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shap--shap/notebooks/tabular_examples/linear_models/Sentiment Analysis with Logistic Regression.ipynb
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wehub-resource-sync 9d4c7d16ba chore: import upstream snapshot with attribution
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"# Sentiment Analysis with Logistic Regression\n",
"\n",
"This gives a simple example of explaining a linear logistic regression sentiment analysis model using shap. Note that with a linear model, the SHAP value of feature $i$ for the prediction $f(x)$ (assuming feature independence) is just $\\phi_i = \\beta_i \\cdot (x_i - E[x_i])$. Since we are explaining a logistic regression model, the units of the SHAP values will be in the log-odds space.\n",
"\n",
"The dataset we are using is the classic IMDB dataset from [this paper](http://www.aclweb.org/anthology/P11-1015). When explaining the model, it is interesting to observe how the words that are absent from the text are sometimes just as important as those that are present."
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n.childContextTypes?u(\"107\",this.getName()||\"ReactCompositeComponent\"):void 0;for(var i in e)i in n.childContextTypes?void 0:u(\"108\",this.getName()||\"ReactCompositeComponent\",i);return c({},t,e)}return t},_checkContextTypes:function(t,e,n){},receiveComponent:function(t,e,n){var r=this._currentElement,i=this._context;this._pendingElement=null,this.updateComponent(e,r,t,i,n)},performUpdateIfNecessary:function(t){null!=this._pendingElement?v.receiveComponent(this,this._pendingElement,t,this._context):null!==this._pendingStateQueue||this._pendingForceUpdate?this.updateComponent(t,this._currentElement,this._currentElement,this._context,this._context):this._updateBatchNumber=null},updateComponent:function(t,e,n,r,i){var o=this._instance;null==o?u(\"136\",this.getName()||\"ReactCompositeComponent\"):void 0;var a,c=!1;this._context===i?a=o.context:(a=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,a);var f=this._processPendingState(l,a),p=!0;this._pendingForceUpdate||(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,a):this._compositeType===_.PureClass&&(p=!m(s,l)||!m(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,a,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=a)},_processPendingState:function(t,e){var n=this._instance,r=this._pendingStateQueue,i=this._pendingReplaceState;if(this._pendingReplaceState=!1,this._pendingStateQueue=null,!r)return n.state;if(i&&1===r.length)return r[0];for(var o=c({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var u=r[a];c(o,\"function\"==typeof u?u.call(n,o,t,e):u)}return o},_performComponentUpdate:function(t,e,n,r,i,o){var a,u,c,s=this._instance,l=Boolean(s.componentDidUpdate);l&&(a=s.props,u=s.state,c=s.context),s.componentWillUpdate&&s.componentWillUpdate(e,n,r),this._currentElement=t,this._context=o,s.props=e,s.state=n,s.context=r,this._updateRenderedComponent(i,o),l&&i.getReactMountReady().enqueue(s.componentDidUpdate.bind(s,a,u,c),s)},_updateRenderedComponent:function(t,e){var n=this._renderedComponent,r=n._currentElement,i=this._renderValidatedComponent(),o=0;if(y(r,i))v.receiveComponent(n,i,t,this._processChildContext(e));else{var a=v.getHostNode(n);v.unmountComponent(n,!1);var u=d.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==d.EMPTY);this._renderedComponent=c;var s=v.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){l.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t,e=this._instance;return t=e.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==_.StatelessFunctional){f.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{f.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t||t===!1||s.isValidElement(t)?void 0:u(\"109\",this.getName()||\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n?u(\"110\"):void 0;var r=e.getPublicInstance(),i=n.refs===g?n.refs={}:n.refs;i[t]=r},detachRef:function(t){var e=this.getPublicInstance().refs;delete e[t]},getName:function(){var t=this._currentElement.type,e=this._instance&&this._instance.constructor;return t.displayName||e&&e.displayName||t.name||e&&e.name||null},getPublicInstance:function(){var t=this._instance;return this._compositeType===_.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=x},function(t,e,n){\"use strict\";var r=n(4),i=n(358),o=n(163),a=n(24),u=n(11),c=n(371),s=n(387),l=n(167),f=n(395);n(1);i.inject();var p={findDOMNode:s,render:o.render,unmountComponentAtNode:o.unmountComponentAtNode,version:c,unstable_batchedUpdates:u.batchedUpdates,unstable_renderSubtreeIntoContainer:f};\"undefined\"!=typeof __REACT_DEVTOOLS_GLOBAL_HOOK__&&\"function\"==typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.inject&&__REACT_DEVTOOLS_GLOBAL_HOOK__.inject({ComponentTree:{getClosestInstanceFromNode:r.getClosestInstanceFromNode,getNodeFromInstance:function(t){return t._renderedComponent&&(t=l(t)),t?r.getNodeFromInstance(t):null}},Mount:o,Reconciler:a});t.exports=p},function(t,e,n){\"use strict\";function r(t){if(t){var e=t._currentElement._owner||null;if(e){var n=e.getName();if(n)return\" This DOM node was rendered by `\"+n+\"`.\"}}return\"\"}function i(t,e){e&&(G[t._tag]&&(null!=e.children||null!=e.dangerouslySetInnerHTML?v(\"137\",t._tag,t._currentElement._owner?\" Check the render method of \"+t._currentElement._owner.getName()+\".\":\"\"):void 0),null!=e.dangerouslySetInnerHTML&&(null!=e.children?v(\"60\"):void 0,\"object\"==typeof e.dangerouslySetInnerHTML&&V in e.dangerouslySetInnerHTML?void 0:v(\"61\")),null!=e.style&&\"object\"!=typeof e.style?v(\"62\",r(t)):void 0)}function o(t,e,n,r){if(!(r instanceof I)){var i=t._hostContainerInfo,o=i._node&&i._node.nodeType===H,u=o?i._node:i._ownerDocument;F(e,u),r.getReactMountReady().enqueue(a,{inst:t,registrationName:e,listener:n})}}function a(){var t=this;C.putListener(t.inst,t.registrationName,t.listener)}function u(){var t=this;S.postMountWrapper(t)}function c(){var t=this;A.postMountWrapper(t)}function s(){var t=this;P.postMountWrapper(t)}function l(){var t=this;t._rootNodeID?void 0:v(\"63\");var e=U(t);switch(e?void 0:v(\"64\"),t._tag){case\"iframe\":case\"object\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"video\":case\"audio\":t._wrapperState.listeners=[];for(var n in q)q.hasOwnProperty(n)&&t._wrapperState.listeners.push(k.trapBubbledEvent(n,q[n],e));break;case\"source\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e),k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topReset\",\"reset\",e),k.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function f(){N.postUpdateWrapper(this)}function p(t){Z.call(X,t)||($.test(t)?void 0:v(\"65\",t),X[t]=!0)}function h(t,e){return t.indexOf(\"-\")>=0||null!=e.is}function d(t){var e=t.type;p(e),this._currentElement=t,this._tag=e.toLowerCase(),this._namespaceURI=null,this._renderedChildren=null,this._previousStyle=null,this._previousStyleCopy=null,this._hostNode=null,this._hostParent=null,this._rootNodeID=0,this._domID=0,this._hostContainerInfo=null,this._wrapperState=null,this._topLevelWrapper=null,this._flags=0}var v=n(2),g=n(3),m=n(332),y=n(334),_=n(20),b=n(82),x=n(21),w=n(156),C=n(22),M=n(83),k=n(51),E=n(157),T=n(4),S=n(351),P=n(352),N=n(158),A=n(355),O=(n(9),n(364)),I=n(369),D=(n(8),n(54)),R=(n(0),n(94),n(80),n(96),n(1),E),L=C.deleteListener,U=T.getNodeFromInstance,F=k.listenTo,j=M.registrationNameModules,B={string:!0,number:!0},W=\"style\",V=\"__html\",z={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},H=11,q={topAbort:\"abort\",topCanPlay:\"canplay\",topCanPlayThrough:\"canplaythrough\",topDurationChange:\"durationchange\",topEmptied:\"emptied\",topEncrypted:\"encrypted\",topEnded:\"ended\",topError:\"error\",topLoadedData:\"loadeddata\",topLoadedMetadata:\"loadedmetadata\",topLoadStart:\"loadstart\",topPause:\"pause\",topPlay:\"play\",topPlaying:\"playing\",topProgress:\"progress\",topRateChange:\"ratechange\",topSeeked:\"seeked\",topSeeking:\"seeking\",topStalled:\"stalled\",topSuspend:\"suspend\",topTimeUpdate:\"timeupdate\",topVolumeChange:\"volumechange\",topWaiting:\"waiting\"},Y={area:!0,base:!0,br:!0,col:!0,embed:!0,hr:!0,img:!0,input:!0,keygen:!0,link:!0,meta:!0,param:!0,source:!0,track:!0,wbr:!0},K={listing:!0,pre:!0,textarea:!0},G=g({menuitem:!0},Y),$=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]*$/,X={},Z={}.hasOwnProperty,Q=1;d.displayName=\"ReactDOMComponent\",d.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=Q++,this._domID=n._idCounter++,this._hostParent=e,this._hostContainerInfo=n;var o=this._currentElement.props;switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":this._wrapperState={listeners:null},t.getReactMountReady().enqueue(l,this);break;case\"input\":S.mountWrapper(this,o,e),o=S.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"option\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o);break;case\"select\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"textarea\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o),t.getReactMountReady().enqueue(l,this)}i(this,o);var a,f;null!=e?(a=e._namespaceURI,f=e._tag):n._tag&&(a=n._namespaceURI,f=n._tag),(null==a||a===b.svg&&\"foreignobject\"===f)&&(a=b.html),a===b.html&&(\"svg\"===this._tag?a=b.svg:\"math\"===this._tag&&(a=b.mathml)),this._namespaceURI=a;var p;if(t.useCreateElement){var h,d=n._ownerDocument;if(a===b.html)if(\"script\"===this._tag){var v=d.createElement(\"div\"),g=this._currentElement.type;v.innerHTML=\"<\"+g+\"></\"+g+\">\",h=v.removeChild(v.firstChild)}else h=o.is?d.createElement(this._currentElement.type,o.is):d.createElement(this._currentElement.type);else h=d.createElementNS(a,this._currentElement.type);T.precacheNode(this,h),this._flags|=R.hasCachedChildNodes,this._hostParent||w.setAttributeForRoot(h),this._updateDOMProperties(null,o,t);var y=_(h);this._createInitialChildren(t,o,r,y),p=y}else{var x=this._createOpenTagMarkupAndPutListeners(t,o),C=this._createContentMarkup(t,o,r);p=!C&&Y[this._tag]?x+\"/>\":x+\">\"+C+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"select\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return p},_createOpenTagMarkupAndPutListeners:function(t,e){var n=\"<\"+this._currentElement.type;for(var r in e)if(e.hasOwnProperty(r)){var i=e[r];if(null!=i)if(j.hasOwnProperty(r))i&&o(this,r,i,t);else{r===W&&(i&&(i=this._previousStyleCopy=g({},e.style)),i=y.createMarkupForStyles(i,this));var a=null;null!=this._tag&&h(this._tag,e)?z.hasOwnProperty(r)||(a=w.createMarkupForCustomAttribute(r,i)):a=w.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent||(n+=\" \"+w.createMarkupForRoot()),n+=\" \"+w.createMarkupForID(this._domID))},_createContentMarkup:function(t,e,n){var r=\"\",i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&(r=i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=D(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return K[this._tag]&&\"\\n\"===r.charAt(0)?\"\\n\"+r:r},_createInitialChildren:function(t,e,n,r){var i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&_.queueHTML(r,i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&_.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)_.queueChild(r,u[c])}},receiveComponent:function(t,e,n){var r=this._currentElement;this._currentElement=t,this.updateComponent(e,r,t,n)},updateComponent:function(t,e,n,r){var o=e.props,a=this._currentElement.props;switch(this._tag){case\"input\":o=S.getHostProps(this,o),a=S.getHostProps(this,a);break;case\"option\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"select\":o=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"textarea\":o=A.getHostProps(this,o),a=A.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":S.updateWrapper(this);break;case\"textarea\":A.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(f,this)}},_updateDOMProperties:function(t,e,n){var r,i,a;for(r in t)if(!e.hasOwnProperty(r)&&t.hasOwnProperty(r)&&null!=t[r])if(r===W){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a||{},a[i]=\"\");this._previousStyleCopy=null}else j.hasOwnProperty(r)?t[r]&&L(this,r):h(this._tag,t)?z.hasOwnProperty(r)||w.deleteValueForAttribute(U(this),r):(x.properties[r]||x.isCustomAttribute(r))&&w.deleteValueForProperty(U(this),r);for(r in e){var c=e[r],s=r===W?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c||null!=s))if(r===W)if(c?c=this._previousStyleCopy=g({},c):this._previousStyleCopy=null,s){for(i in s)!s.hasOwnProperty(i)||c&&c.hasOwnProperty(i)||(a=a||{},a[i]=\"\");for(i in c)c.hasOwnProperty(i)&&s[i]!==c[i]&&(a=a||{},a[i]=c[i])}else a=c;else if(j.hasOwnProperty(r))c?o(this,r,c,n):s&&L(this,r);else if(h(this._tag,e))z.hasOwnProperty(r)||w.setValueForAttribute(U(this),r,c);else if(x.properties[r]||x.isCustomAttribute(r)){var l=U(this);null!=c?w.setValueForProperty(l,r,c):w.deleteValueForProperty(l,r)}}a&&y.setValueForStyles(U(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=B[typeof t.children]?t.children:null,o=B[typeof e.children]?e.children:null,a=t.dangerouslySetInnerHTML&&t.dangerouslySetInnerHTML.__html,u=e.dangerouslySetInnerHTML&&e.dangerouslySetInnerHTML.__html,c=null!=i?null:t.children,s=null!=o?null:e.children,l=null!=i||null!=a,f=null!=o||null!=u;null!=c&&null==s?this.updateChildren(null,n,r):l&&!f&&this.updateTextContent(\"\"),null!=o?i!==o&&this.updateTextContent(\"\"+o):null!=u?a!==u&&this.updateMarkup(\"\"+u):null!=s&&this.updateChildren(s,n,r)},getHostNode:function(){return U(this)},unmountComponent:function(t){switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":var e=this._wrapperState.listeners;if(e)for(var n=0;n<e.length;n++)e[n].remove();break;case\"html\":case\"head\":case\"body\":v(\"66\",this._tag)}this.unmountChildren(t),T.uncacheNode(this),C.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return U(this)}},g(d.prototype,d.Mixin,O.Mixin),t.exports=d},function(t,e,n){\"use strict\";function r(t,e){var n={_topLevelWrapper:t,_idCounter:1,_ownerDocument:e?e.nodeType===i?e:e.ownerDocument:null,_node:e,_tag:e?e.nodeName.toLowerCase():null,_namespaceURI:e?e.namespaceURI:null};return n}var i=(n(96),9);t.exports=r},function(t,e,n){\"use strict\";var r=n(3),i=n(20),o=n(4),a=function(t){this._currentElement=null,this._hostNode=null,this._hostParent=null,this._hostContainerInfo=null,this._domID=0};r(a.prototype,{mountComponent:function(t,e,n,r){var a=n._idCounter++;this._domID=a,this._hostParent=e,this._hostContainerInfo=n;var u=\" react-empty: \"+this._domID+\" \";if(t.useCreateElement){var c=n._ownerDocument,s=c.createComment(u);return o.precacheNode(this,s),i(s)}return t.renderToStaticMarkup?\"\":\"<!--\"+u+\"-->\"},receiveComponent:function(){},getHostNode:function(){return o.getNodeFromInstance(this)},unmountComponent:function(){o.uncacheNode(this)}}),t.exports=a},function(t,e,n){\"use strict\";var r={useCreateElement:!0,useFiber:!1};t.exports=r},function(t,e,n){\"use strict\";var r=n(81),i=n(4),o={dangerouslyProcessChildrenUpdates:function(t,e){var n=i.getNodeFromInstance(t);r.processUpdates(n,e)}};t.exports=o},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&f.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=c.executeOnChange(e,t);l.asap(r,this);var i=e.name;if(\"radio\"===e.type&&null!=i){for(var a=s.getNodeFromInstance(this),u=a;u.parentNode;)u=u.parentNode;for(var f=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<f.length;p++){var h=f[p];if(h!==a&&h.form===a.form){var d=s.getInstanceFromNode(h);d?void 0:o(\"90\"),l.asap(r,d)}}}return n}var o=n(2),a=n(3),u=n(156),c=n(85),s=n(4),l=n(11),f=(n(0),n(1),{getHostProps:function(t,e){var n=c.getValue(e),r=c.getChecked(e),i=a({type:void 0,step:void 0,min:void 0,max:void 0},e,{defaultChecked:void 0,defaultValue:void 0,value:null!=n?n:t._wrapperState.initialValue,checked:null!=r?r:t._wrapperState.initialChecked,onChange:t._wrapperState.onChange});return i},mountWrapper:function(t,e){var n=e.defaultValue;t._wrapperState={initialChecked:null!=e.checked?e.checked:e.defaultChecked,initialValue:null!=e.value?e.value:n,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&u.setValueForProperty(s.getNodeFromInstance(t),\"checked\",n||!1);var r=s.getNodeFromInstance(t),i=c.getValue(e);if(null!=i){var o=\"\"+i;o!==r.value&&(r.value=o)}else null==e.value&&null!=e.defaultValue&&r.defaultValue!==\"\"+e.defaultValue&&(r.defaultValue=\"\"+e.defaultValue),null==e.checked&&null!=e.defaultChecked&&(r.defaultChecked=!!e.defaultChecked)},postMountWrapper:function(t){var e=t._currentElement.props,n=s.getNodeFromInstance(t);switch(e.type){case\"submit\":case\"reset\":break;case\"color\":case\"date\":case\"datetime\":case\"datetime-local\":case\"month\":case\"time\":case\"week\":n.value=\"\",n.value=n.defaultValue;break;default:n.value=n.value}var r=n.name;\"\"!==r&&(n.name=\"\"),n.defaultChecked=!n.defaultChecked,n.defaultChecked=!n.defaultChecked,\"\"!==r&&(n.name=r)}});t.exports=f},function(t,e,n){\"use strict\";function r(t){var e=\"\";return o.Children.forEach(t,function(t){null!=t&&(\"string\"==typeof t||\"number\"==typeof t?e+=t:c||(c=!0))}),e}var i=n(3),o=n(26),a=n(4),u=n(158),c=(n(1),!1),s={mountWrapper:function(t,e,n){var i=null;if(null!=n){var o=n;\"optgroup\"===o._tag&&(o=o._hostParent),null!=o&&\"select\"===o._tag&&(i=u.getSelectValueContext(o))}var a=null;if(null!=i){var c;if(c=null!=e.value?e.value+\"\":r(e.children),a=!1,Array.isArray(i)){for(var s=0;s<i.length;s++)if(\"\"+i[s]===c){a=!0;break}}else a=\"\"+i===c}t._wrapperState={selected:a}},postMountWrapper:function(t){var e=t._currentElement.props;if(null!=e.value){var n=a.getNodeFromInstance(t);n.setAttribute(\"value\",e.value)}},getHostProps:function(t,e){var n=i({selected:void 0,children:void 0},e);null!=t._wrapperState.selected&&(n.selected=t._wrapperState.selected);var o=r(e.children);return o&&(n.children=o),n}};t.exports=s},function(t,e,n){\"use strict\";function r(t,e,n,r){return t===n&&e===r}function i(t){var e=document.selection,n=e.createRange(),r=n.text.length,i=n.duplicate();i.moveToElementText(t),i.setEndPoint(\"EndToStart\",n);var o=i.text.length,a=o+r;return{start:o,end:a}}function o(t){var e=window.getSelection&&window.getSelection();if(!e||0===e.rangeCount)return null;var n=e.anchorNode,i=e.anchorOffset,o=e.focusNode,a=e.focusOffset,u=e.getRangeAt(0);try{u.startContainer.nodeType,u.endContainer.nodeType}catch(t){return null}var c=r(e.anchorNode,e.anchorOffset,e.focusNode,e.focusOffset),s=c?0:u.toString().length,l=u.cloneRange();l.selectNodeContents(t),l.setEnd(u.startContainer,u.startOffset);var f=r(l.startContainer,l.startOffset,l.endContainer,l.endOffset),p=f?0:l.toString().length,h=p+s,d=document.createRange();d.setStart(n,i),d.setEnd(o,a);var v=d.collapsed;return{start:v?h:p,end:v?p:h}}function a(t,e){var n,r,i=document.selection.createRange().duplicate();void 0===e.end?(n=e.start,r=n):e.start>e.end?(n=e.end,r=e.start):(n=e.start,r=e.end),i.moveToElementText(t),i.moveStart(\"character\",n),i.setEndPoint(\"EndToStart\",i),i.moveEnd(\"character\",r-n),i.select()}function u(t,e){if(window.getSelection){var n=window.getSelection(),r=t[l()].length,i=Math.min(e.start,r),o=void 0===e.end?i:Math.min(e.end,r);if(!n.extend&&i>o){var a=o;o=i,i=a}var u=s(t,i),c=s(t,o);if(u&&c){var f=document.createRange();f.setStart(u.node,u.offset),n.removeAllRanges(),i>o?(n.addRange(f),n.extend(c.node,c.offset)):(f.setEnd(c.node,c.offset),n.addRange(f))}}}var c=n(6),s=n(392),l=n(168),f=c.canUseDOM&&\"selection\"in document&&!(\"getSelection\"in window),p={getOffsets:f?i:o,setOffsets:f?a:u};t.exports=p},function(t,e,n){\"use strict\";var r=n(2),i=n(3),o=n(81),a=n(20),u=n(4),c=n(54),s=(n(0),n(96),function(t){this._currentElement=t,this._stringText=\"\"+t,this._hostNode=null,this._hostParent=null,this._domID=0,this._mountIndex=0,this._closingComment=null,this._commentNodes=null});i(s.prototype,{mountComponent:function(t,e,n,r){var i=n._idCounter++,o=\" react-text: \"+i+\" \",s=\" /react-text \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var l=n._ownerDocument,f=l.createComment(o),p=l.createComment(s),h=a(l.createDocumentFragment());return 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r(){this._rootNodeID&&l.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=u.executeOnChange(e,t);return s.asap(r,this),n}var o=n(2),a=n(3),u=n(85),c=n(4),s=n(11),l=(n(0),n(1),{getHostProps:function(t,e){null!=e.dangerouslySetInnerHTML?o(\"91\"):void 0;var n=a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange});return n},mountWrapper:function(t,e){var n=u.getValue(e),r=n;if(null==n){var a=e.defaultValue,c=e.children;null!=c&&(null!=a?o(\"92\"):void 0,Array.isArray(c)&&(c.length<=1?void 0:o(\"93\"),c=c[0]),a=\"\"+c),null==a&&(a=\"\"),r=a}t._wrapperState={initialValue:\"\"+r,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=c.getNodeFromInstance(t),r=u.getValue(e);if(null!=r){var i=\"\"+r;i!==n.value&&(n.value=i),null==e.defaultValue&&(n.defaultValue=i)}null!=e.defaultValue&&(n.defaultValue=e.defaultValue)},postMountWrapper:function(t){var e=c.getNodeFromInstance(t),n=e.textContent;\nn===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t?void 0:c(\"33\"),\"_hostNode\"in e?void 0:c(\"33\");for(var n=0,r=t;r;r=r._hostParent)n++;for(var i=0,o=e;o;o=o._hostParent)i++;for(;n-i>0;)t=t._hostParent,n--;for(;i-n>0;)e=e._hostParent,i--;for(var a=n;a--;){if(t===e)return t;t=t._hostParent,e=e._hostParent}return null}function i(t,e){\"_hostNode\"in t?void 0:c(\"35\"),\"_hostNode\"in e?void 0:c(\"35\");for(;e;){if(e===t)return!0;e=e._hostParent}return!1}function o(t){return\"_hostNode\"in t?void 0:c(\"36\"),t._hostParent}function a(t,e,n){for(var r=[];t;)r.push(t),t=t._hostParent;var i;for(i=r.length;i-- >0;)e(r[i],\"captured\",n);for(i=0;i<r.length;i++)e(r[i],\"bubbled\",n)}function u(t,e,n,i,o){for(var a=t&&e?r(t,e):null,u=[];t&&t!==a;)u.push(t),t=t._hostParent;for(var c=[];e&&e!==a;)c.push(e),e=e._hostParent;var 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r(){C||(C=!0,y.EventEmitter.injectReactEventListener(m),y.EventPluginHub.injectEventPluginOrder(u),y.EventPluginUtils.injectComponentTree(p),y.EventPluginUtils.injectTreeTraversal(d),y.EventPluginHub.injectEventPluginsByName({SimpleEventPlugin:w,EnterLeaveEventPlugin:c,ChangeEventPlugin:a,SelectEventPlugin:x,BeforeInputEventPlugin:o}),y.HostComponent.injectGenericComponentClass(f),y.HostComponent.injectTextComponentClass(v),y.DOMProperty.injectDOMPropertyConfig(i),y.DOMProperty.injectDOMPropertyConfig(s),y.DOMProperty.injectDOMPropertyConfig(b),y.EmptyComponent.injectEmptyComponentFactory(function(t){return new h(t)}),y.Updates.injectReconcileTransaction(_),y.Updates.injectBatchingStrategy(g),y.Component.injectEnvironment(l))}var i=n(331),o=n(333),a=n(335),u=n(337),c=n(338),s=n(341),l=n(343),f=n(346),p=n(4),h=n(348),d=n(356),v=n(354),g=n(357),m=n(361),y=n(362),_=n(367),b=n(372),x=n(373),w=n(374),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof 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v={_enabled:!0,_handleTopLevel:null,WINDOW_HANDLE:s.canUseDOM?window:null,setHandleTopLevel:function(t){v._handleTopLevel=t},setEnabled:function(t){v._enabled=!!t},isEnabled:function(){return v._enabled},trapBubbledEvent:function(t,e,n){return n?c.listen(n,e,v.dispatchEvent.bind(null,t)):null},trapCapturedEvent:function(t,e,n){return n?c.capture(n,e,v.dispatchEvent.bind(null,t)):null},monitorScrollValue:function(t){var e=a.bind(null,t);c.listen(window,\"scroll\",e)},dispatchEvent:function(t,e){if(v._enabled){var n=i.getPooled(t,e);try{p.batchedUpdates(o,n)}finally{i.release(n)}}}};t.exports=v},function(t,e,n){\"use strict\";var r=n(21),i=n(22),o=n(50),a=n(86),u=n(159),c=n(51),s=n(161),l=n(11),f={Component:a.injection,DOMProperty:r.injection,EmptyComponent:u.injection,EventPluginHub:i.injection,EventPluginUtils:o.injection,EventEmitter:c.injection,HostComponent:s.injection,Updates:l.injection};t.exports=f},function(t,e,n){\"use strict\";var r=n(385),i=/\\/?>/,o=/^<\\!\\-\\-/,a={CHECKSUM_ATTR_NAME:\"data-react-checksum\",addChecksumToMarkup:function(t){var e=r(t);return o.test(t)?t:t.replace(i,\" \"+a.CHECKSUM_ATTR_NAME+'=\"'+e+'\"$&')},canReuseMarkup:function(t,e){var n=e.getAttribute(a.CHECKSUM_ATTR_NAME);n=n&&parseInt(n,10);var i=r(t);return i===n}};t.exports=a},function(t,e,n){\"use strict\";function r(t,e,n){return{type:\"INSERT_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:n,afterNode:e}}function i(t,e,n){return{type:\"MOVE_EXISTING\",content:null,fromIndex:t._mountIndex,fromNode:p.getHostNode(t),toIndex:n,afterNode:e}}function o(t,e){return{type:\"REMOVE_NODE\",content:null,fromIndex:t._mountIndex,fromNode:e,toIndex:null,afterNode:null}}function a(t){return{type:\"SET_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function u(t){return{type:\"TEXT_CONTENT\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function c(t,e){return e&&(t=t||[],t.push(e)),t}function s(t,e){f.processChildrenUpdates(t,e)}var l=n(2),f=n(86),p=(n(40),n(9),n(15),n(24)),h=n(342),d=(n(8),n(388)),v=(n(0),{Mixin:{_reconcilerInstantiateChildren:function(t,e,n){return h.instantiateChildren(t,e,n)},_reconcilerUpdateChildren:function(t,e,n,r,i,o){var a,u=0;return a=d(e,u),h.updateChildren(t,a,n,r,i,this,this._hostContainerInfo,o,u),a},mountChildren:function(t,e,n){var r=this._reconcilerInstantiateChildren(t,e,n);this._renderedChildren=r;var i=[],o=0;for(var a in r)if(r.hasOwnProperty(a)){var u=r[a],c=0,s=p.mountComponent(u,e,this,this._hostContainerInfo,n,c);u._mountIndex=o++,i.push(s)}return i},updateTextContent:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[u(t)];s(this,r)},updateMarkup:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[a(t)];s(this,r)},updateChildren:function(t,e,n){this._updateChildren(t,e,n)},_updateChildren:function(t,e,n){var r=this._renderedChildren,i={},o=[],a=this._reconcilerUpdateChildren(r,t,o,i,e,n);if(a||r){var u,l=null,f=0,h=0,d=0,v=null;for(u in a)if(a.hasOwnProperty(u)){var g=r&&r[u],m=a[u];g===m?(l=c(l,this.moveChild(g,v,f,h)),h=Math.max(g._mountIndex,h),g._mountIndex=f):(g&&(h=Math.max(g._mountIndex,h)),l=c(l,this._mountChildAtIndex(m,o[d],v,f,e,n)),d++),f++,v=p.getHostNode(m)}for(u in i)i.hasOwnProperty(u)&&(l=c(l,this._unmountChild(r[u],i[u])));l&&s(this,l),this._renderedChildren=a}},unmountChildren:function(t){var e=this._renderedChildren;h.unmountChildren(e,t),this._renderedChildren=null},moveChild:function(t,e,n,r){if(t._mountIndex<r)return i(t,e,n)},createChild:function(t,e,n){return r(n,e,t._mountIndex)},removeChild:function(t,e){return o(t,e)},_mountChildAtIndex:function(t,e,n,r,i,o){return t._mountIndex=r,this.createChild(t,n,e)},_unmountChild:function(t,e){var n=this.removeChild(t,e);return t._mountIndex=null,n}}});t.exports=v},function(t,e,n){\"use strict\";function r(t){return!(!t||\"function\"!=typeof t.attachRef||\"function\"!=typeof t.detachRef)}var i=n(2),o=(n(0),{addComponentAsRefTo:function(t,e,n){r(n)?void 0:i(\"119\"),n.attachRef(e,t)},removeComponentAsRefFrom:function(t,e,n){r(n)?void 0:i(\"120\");var o=n.getPublicInstance();o&&o.refs[e]===t.getPublicInstance()&&n.detachRef(e)}});t.exports=o},function(t,e,n){\"use strict\";var r=\"SECRET_DO_NOT_PASS_THIS_OR_YOU_WILL_BE_FIRED\";t.exports=r},function(t,e,n){\"use strict\";function r(t){this.reinitializeTransaction(),this.renderToStaticMarkup=!1,this.reactMountReady=o.getPooled(null),this.useCreateElement=t}var i=n(3),o=n(155),a=n(17),u=n(51),c=n(162),s=(n(9),n(53)),l=n(88),f={initialize:c.getSelectionInformation,close:c.restoreSelection},p={initialize:function(){var t=u.isEnabled();return u.setEnabled(!1),t},close:function(t){u.setEnabled(t)}},h={initialize:function(){this.reactMountReady.reset()},close:function(){this.reactMountReady.notifyAll()}},d=[f,p,h],v={getTransactionWrappers:function(){return d},getReactMountReady:function(){return this.reactMountReady},getUpdateQueue:function(){return l},checkpoint:function(){return this.reactMountReady.checkpoint()},rollback:function(t){this.reactMountReady.rollback(t)},destructor:function(){o.release(this.reactMountReady),this.reactMountReady=null}};i(r.prototype,s,v),a.addPoolingTo(r),t.exports=r},function(t,e,n){\"use strict\";function r(t,e,n){\"function\"==typeof t?t(e.getPublicInstance()):o.addComponentAsRefTo(e,t,n)}function i(t,e,n){\"function\"==typeof t?t(null):o.removeComponentAsRefFrom(e,t,n)}var o=n(365),a={};a.attachRefs=function(t,e){if(null!==e&&\"object\"==typeof e){var n=e.ref;null!=n&&r(n,t,e._owner)}},a.shouldUpdateRefs=function(t,e){var n=null,r=null;null!==t&&\"object\"==typeof 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"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import sklearn\n",
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
"from sklearn.metrics import classification_report\n",
"from sklearn.model_selection import train_test_split\n",
"\n",
"import shap\n",
"\n",
"np.random.seed(101)\n",
"shap.initjs()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the IMDB dataset"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"corpus, y = shap.datasets.imdb()\n",
"corpus_train, corpus_test, y_train, y_test = train_test_split(corpus, y, test_size=0.2, random_state=7)\n",
"\n",
"vectorizer = TfidfVectorizer(min_df=10)\n",
"X_train = vectorizer.fit_transform(\n",
" corpus_train\n",
").toarray() # sparse also works but Explanation slicing is not yet supported\n",
"X_test = vectorizer.transform(corpus_test).toarray()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fit a linear logistic regression model"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" False 0.84 0.84 0.84 2426\n",
" True 0.85 0.85 0.85 2574\n",
"\n",
" accuracy 0.85 5000\n",
" macro avg 0.85 0.85 0.85 5000\n",
"weighted avg 0.85 0.85 0.85 5000\n",
"\n"
]
}
],
"source": [
"model = sklearn.linear_model.LogisticRegression(penalty=\"l2\", C=0.1)\n",
"model.fit(X_train, y_train)\n",
"print(classification_report(y_test, model.predict(X_test)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Explain the linear model"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"explainer = shap.Explainer(model, X_train, feature_names=vectorizer.get_feature_names_out())\n",
"shap_values = explainer(X_test)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Summarize the effect of all the features"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"No data for colormapping provided via 'c'. Parameters 'vmin', 'vmax' will be ignored\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": "<Figure size 800x550 with 2 Axes>"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"shap.plots.beeswarm(shap_values)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Explain the first review's sentiment prediction\n",
"\n",
"Remember that higher SHAP values means the review is more likely to be negative. So in the plots below, the \"red\" features are increasing the chance of a positive review, while the \"blue\" features are lowering the chance. It is interesting to see how what is not present in the text (like `bad=0` below) is often just as important as what is in the text. Note that the values of the features are TF-IDF values."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": "\n<div id='iDC68K9EESY9UC0I2YLZ5'>\n<div style='color: #900; text-align: center;'>\n <b>Visualization omitted, Javascript library not loaded!</b><br>\n Have you run `initjs()` in this notebook? If this notebook was from another\n user you must also trust this notebook (File -> Trust notebook). If you are viewing\n this notebook on github the Javascript has been stripped for security. 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\"bryan\", \"bryant\", \"brynner\", \"bs\", \"bsg\", \"btk\", \"btw\", \"bubble\", \"bubblegum\", \"bubbles\", \"bubbly\", \"buck\", \"bucket\", \"buckets\", \"bucks\", \"bud\", \"budapest\", \"buddhist\", \"buddies\", \"budding\", \"buddy\", \"budget\", \"budgetary\", \"budgeted\", \"budgets\", \"buff\", \"buffalo\", \"buffoon\", \"buffs\", \"buffy\", \"bug\", \"buggy\", \"bugs\", \"build\", \"building\", \"buildings\", \"builds\", \"buildup\", \"built\", \"bulb\", \"bulging\", \"bulk\", \"bull\", \"bulldog\", \"bullet\", \"bullets\", \"bullied\", \"bullies\", \"bullock\", \"bulls\", \"bullshit\", \"bully\", \"bullying\", \"bum\", \"bumbling\", \"bump\", \"bumped\", \"bumping\", \"bumps\", \"bums\", \"bunch\", \"bunker\", \"bunny\", \"bunuel\", \"burden\", \"burdened\", \"bureau\", \"bureaucracy\", \"burgeoning\", \"burgess\", \"burial\", \"buried\", \"buries\", \"burke\", \"burlesque\", \"burn\", \"burned\", \"burnett\", \"burning\", \"burns\", \"burnt\", \"burroughs\", \"burrows\", \"burst\", \"bursting\", \"bursts\", \"burstyn\", \"burt\", \"burton\", \"bury\", \"burying\", \"bus\", \"busby\", \"buscemi\", \"buses\", \"busey\", \"bush\", \"bushes\", \"business\", \"businesses\", \"businessman\", \"businessmen\", \"bust\", \"busted\", \"buster\", \"busting\", \"busy\", \"but\", \"butch\", \"butcher\", \"butchered\", \"butchering\", \"butler\", \"butt\", \"butter\", \"butterfly\", \"button\", \"buttons\", \"butts\", \"buy\", \"buying\", \"buys\", \"buzz\", \"by\", \"bye\", \"bygone\", \"byrne\", \"byron\", \"ca\", \"caan\", \"cab\", \"cabaret\", \"cabin\", \"cabinet\", \"cable\", \"cad\", \"caesar\", \"cafe\", \"cafeteria\", \"caf\\u00e9\", \"cage\", \"caged\", \"cages\", \"cagney\", \"cain\", \"caine\", \"cake\", \"cal\", \"calamity\", \"calculated\", \"calculating\", \"calendar\", \"caliber\", \"calibre\", \"california\", \"call\", \"callahan\", \"called\", \"calling\", \"callous\", \"calls\", \"calm\", \"calmly\", \"calvin\", \"cam\", \"camaraderie\", 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"text/plain": "<shap.plots._force.AdditiveForceVisualizer at 0x7f3ac3c183d0>"
},
"execution_count": 6,
"metadata": {},
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"source": [
"ind = 0\n",
"shap.plots.force(shap_values[ind])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
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"name": "stdout",
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"text": [
"Positive Review:\n",
"\"Twelve Monkeys\" is odd and disturbing, yet being so clever and intelligent at the same time. It cleverly jumps between future and the past, and the story it tells is about a man named James Cole, a convict, who is sent back to the past to gather information about a man-made virus that wiped out 5 billion of the human population on the planet back in 1996. At first Cole is sent back to the year 1990 by accident and by misfortune he is taken to a mental institution where he tries to explain his purpose and where he meets a psychiatrist Dr. Kathryn Railly who tries to help him and a patient named Jeffrey Goines, the insane son of a famous scientist. Being provocative and somehow so sensible, dealing with and between reason and madness, the movie is a definite masterpiece in the history of science-fiction films.<br /><br />The story is just fantastic. It's so original and so entertaining. The screenplay itself written by David and Janet Peoples is inspired by a movie named \"La Jetée\" (1962) which I haven't seen, but I must thank the director and writer of the movie, Chris Marker, for giving such an inspiration for the writers of \"Twelve Monkeys\". I read a little about \"La Jetée\", it's not the same story but it has the same idea, so this is not just a copy of it. David and Janet Peoples have transformed this great deal of inspiration to a modernized story, which tells about this urgent need for people to find a solution for maintaining human existence and it does it in a so beautiful and a realistic way that it's a guaranteed thrill ride from the beginning till the end. The music used in the film is odd and somehow so funny and amusing it doesn't really fit until you really get it and when you do you realise that it's so compelling, composed by Paul Buckmaster.<br /><br />Terry Gilliam, who we remember from Monty Python, as the director of the movie was a real surprise for me, as I really never thought him as a director type of a person. I know he has directed movies before, but I really couldn't believe that he could make something this magnificent. It shouldn't be a surprise though, as he does an amazing job. You can still sense that same weirdness as in the Python's, but for me the directing is pretty much flawless though in its odd way of describing things it also makes some scenes strangely disturbing. Yes, it is indeed odd, weird, bizarre and disturbing, so it also makes the movie a bit heavy too, so the weak minded viewers will probably find it hard to watch the movie all the way through. It's not as heavy as you could imagine, but it just has these certain things which in their own purpose are sometimes pretty severe to watch. Despite that, the movie holds this pure intelligence inside it and through flashbacks, dreams, jumps between the past and the future it mixes up the whole story in a very clever way and it doesn't even make the plot messy in any part, though it does need concentration from the viewer after all.<br /><br />What comes to acting, well the movie doesn't even go wrong there. The role of James Cole is played by the mighty Bruce Willis, who probably does his best role performance yet to date. Now people may disagree with me, as he did some fine job in for example \"The Sixth Sense\" as well, but for me the role of James Cole was so ideal for Willis and he performs it incredibly well. The character is very well written too, yet performed even better. Cole starts to question his own existence and he deals with himself, starting to question his actual time of living, trying to survive and find the crucial missing piece of the puzzle. By hardship he starts to loose his faith, questioning if he can even trust or believe himself. Other role performances worth mentioning are the performances of Madeleine Stow and Brad Pitt. Stow plays the role of Kathryn Railly, the psychiatrist of James Cole, who sees something strangely familiar in Cole and decides to help him to deal with his madness. She somehow starts to believe Cole's story but as a believer of science she tries to find solutions through it and tries to deal with reason when it comes to unbelievable things. Brad Pitt is so good in the role of Jeffrey Goines and he also does one of his best role performances yet to date. The insane yet hilarious personality of the character brought Pitt even an Oscar nomination for it, so I guess I'm not praising the honestly fabulous performance for nothing.<br /><br />All in all, \"Twelve Monkeys\" is a great science-fiction experience and it will surely be a recommendation for everyone, especially for the sci-fi fans. It includes brilliant characters and superb role performances, especially from Willis and Pitt, and an original and an entertaining story which forms a plot that's so intelligent and clever. Yet being that already mentioned weird and disturbing it definitely captures the viewer's attention by making it interesting and witty. It's also an explosive thriller and it has romance in it too, so it's all that in same package and that makes it one of the best sci-fi motion pictures I've ever seen. Through the odd yet terrific vision of Terry Gilliam it manages to keep itself in balance despite the somewhat bumpy yet somehow stable ride. Hard to explain really, but that's how it is, it's mind blowing.\n",
"\n"
]
}
],
"source": [
"print(\"Positive\" if y_test[ind] else \"Negative\", \"Review:\")\n",
"print(corpus_test[ind])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Explain the second review's sentiment prediction"
]
},
{
"cell_type": "code",
"execution_count": 8,
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\"kate\", \"katherine\", \"kathleen\", \"kathryn\", \"kathy\", \"katie\", \"katsu\", \"kattan\", \"kaufman\", \"kavner\", \"kay\", \"kaye\", \"kazan\", \"keanu\", \"keaton\", \"keeler\", \"keen\", \"keep\", \"keeper\", \"keeping\", \"keeps\", \"kei\", \"keira\", \"keitel\", \"keith\", \"keller\", \"kellerman\", \"kelly\", \"ken\", \"kennedy\", \"kennel\", \"kenneth\", \"kenny\", \"kent\", \"kentucky\", \"kept\", \"kermit\", \"kerr\", \"kerry\", \"ketchup\", \"kevin\", \"key\", \"keyboard\", \"keys\", \"keystone\", \"khan\", \"khanna\", \"kick\", \"kicked\", \"kicker\", \"kicking\", \"kicks\", \"kid\", \"kiddie\", \"kiddies\", \"kidding\", \"kidman\", \"kidnap\", \"kidnapped\", \"kidnappers\", \"kidnapping\", \"kidnaps\", \"kids\", \"kiefer\", \"kill\", \"killed\", \"killer\", \"killers\", \"killing\", \"killings\", \"kills\", \"kilmer\", \"kilter\", \"kim\", \"kimberly\", \"kin\", \"kind\", \"kinda\", \"kindergarten\", \"kindly\", \"kindness\", \"kinds\", \"kinetic\", \"king\", \"kingdom\", \"kings\", \"kingsley\", \"kinky\", \"kinnear\", \"kino\", \"kinski\", \"kipling\", \"kirk\", \"kirsten\", \"kiss\", \"kissed\", \"kisses\", \"kissing\", \"kit\", \"kitamura\", \"kitchen\", \"kitsch\", \"kitschy\", \"kitten\", \"kittens\", \"kitty\", \"klaus\", \"klein\", \"kline\", \"knack\", \"knee\", \"knees\", \"knew\", \"knife\", \"knight\", \"knightley\", \"knightly\", \"knights\", \"knit\", \"knives\", \"knock\", \"knocked\", \"knocking\", \"knockoff\", \"knocks\", \"know\", \"knowing\", \"knowingly\", \"knowledge\", \"knowledgeable\", \"known\", \"knows\", \"knox\", \"knuckle\", \"kolchak\", \"kong\", \"koo\", \"kooky\", \"korda\", \"korea\", \"korean\", \"kothari\", \"kotto\", \"kovacs\", \"kramer\", \"krause\", \"krell\", \"krige\", \"kris\", \"krishna\", \"kristen\", \"kristin\", \"kristofferson\", \"krueger\", \"kruger\", \"kubrick\", \"kudos\", \"kudrow\", \"kumar\", \"kung\", \"kurosawa\", \"kurt\", \"kyle\", \"kylie\", \"la\", \"lab\", \"label\", 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\"lions\", \"liotta\", \"lip\", \"lips\", \"lipstick\", \"liquid\", \"liquor\", \"lisa\", \"list\", \"listed\", \"listen\", \"listened\", \"listener\", \"listening\", \"listens\", \"listing\", \"listings\", \"listless\", \"lists\", \"lit\", \"lite\", \"literal\", \"literally\", \"literary\", \"literate\", \"literature\", \"lithgow\", \"litter\", \"little\", \"liu\", \"liv\", \"live\", \"lived\", \"lively\", \"liven\", \"liver\", \"lives\", \"living\", \"livingston\", \"liz\", \"liza\", \"lizard\", \"lizards\", \"ll\", \"lloyd\", \"lo\", \"loach\", \"load\", \"loaded\", \"loads\", \"loan\", \"loathe\", \"loathing\", \"loathsome\", \"lobby\", \"local\", \"locale\", \"locales\", \"locals\", \"locate\", \"located\", \"location\", \"locations\", \"lock\", \"locke\", \"locked\", \"locker\", \"locking\", \"locks\", \"log\", \"logan\", \"loggia\", \"logic\", \"logical\", \"logically\", \"logo\", \"lohan\", \"lois\", \"lol\", \"lola\", \"lolita\", \"lombard\", \"lommel\", \"lon\", \"london\", 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\"misery\", \"misfire\", \"misfit\", \"misfits\", \"misfortune\", \"misguided\", \"mish\", \"mishaps\", \"mishmash\", \"mislead\", \"misleading\", \"misled\", \"mismatched\", \"misogynistic\", \"misogyny\", \"misplaced\", \"miss\", \"missed\", \"misses\", \"missile\", \"missiles\", \"missing\", \"mission\", \"missionary\", \"missions\", \"missouri\", \"mist\", \"mistake\", \"mistaken\", \"mistakenly\", \"mistakes\", \"mister\", \"mistreated\", \"mistress\", \"misty\", \"misunderstand\", \"misunderstanding\", \"misunderstandings\", \"misunderstood\", \"misused\", \"mitch\", \"mitchell\", \"mitchum\", \"mix\", \"mixed\", \"mixes\", \"mixing\", \"mixture\", \"miyazaki\", \"mm\", \"mo\", \"moan\", \"moaning\", \"moans\", \"mob\", \"mobile\", \"mobster\", \"mobsters\", \"mock\", \"mocked\", \"mockery\", \"mocking\", \"mockumentary\", \"mode\", \"model\", \"modeled\", \"modeling\", \"models\", \"moderate\", \"moderately\", \"modern\", \"modest\", \"modesty\", \"modicum\", \"modine\", 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\"morita\", \"mormon\", \"mormons\", \"morning\", \"moron\", \"moronic\", \"morons\", \"morose\", \"morphed\", \"morphs\", \"morricone\", \"morris\", \"morrow\", \"morse\", \"mortal\", \"mortality\", \"mortally\", \"mortensen\", \"mortimer\", \"morton\", \"moscow\", \"moses\", \"moss\", \"most\", \"mostel\", \"mostly\", \"motel\", \"mother\", \"mothers\", \"motif\", \"motifs\", \"motion\", \"motions\", \"motivated\", \"motivation\", \"motivations\", \"motive\", \"motives\", \"motley\", \"motor\", \"motorcycle\", \"moulin\", \"mount\", \"mountain\", \"mountains\", \"mounted\", \"mounting\", \"mourning\", \"mouse\", \"moustache\", \"mouth\", \"mouthed\", \"mouths\", \"move\", \"moved\", \"movement\", \"movements\", \"moves\", \"movie\", \"moviegoer\", \"moviegoers\", \"movies\", \"moving\", \"mower\", \"mpaa\", \"mph\", \"mr\", \"mrs\", \"ms\", \"mst\", \"mst3k\", \"mtv\", \"much\", \"muck\", \"mud\", \"muddled\", \"muddy\", \"mug\", \"mugging\", \"mulder\", \"mulholland\", \"muller\", 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"text/plain": "<shap.plots._force.AdditiveForceVisualizer at 0x7f3a4daef150>"
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind = 1\n",
"shap.plots.force(shap_values[ind])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Negative Review:\n",
"I don't understand the positive comments made about this film. It is cheap and nasty on all levels and I cannot understand how it ever got made.<br /><br />Cartoon characters abound - Sue's foul-mouthed, alcoholic, layabout, Irish father being a prime example. None of the characters are remotely sympathetic - except, briefly, for Sue's Asian boyfriend but even he then turns out to be capable of domestic violence! As desperately unattractive as they both are, I've no idea why either Rita and/or Sue would throw themselves at a consummate creep like Bob - but given that they do, why should I be expected to care what happens to them? So many reviews keep carping on about how \"realistic\" it is. If that is true, it is a sad reflection on society but no reason to put it on film.<br /><br />I didn't like the film at all.\n",
"\n"
]
}
],
"source": [
"print(\"Positive\" if y_test[ind] else \"Negative\", \"Review:\")\n",
"print(corpus_test[ind])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Explain the third review's sentiment prediction"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2023-07-23T08:57:17.292389446Z",
"start_time": "2023-07-23T08:57:17.226358366Z"
}
},
"outputs": [
{
"data": {
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\"RdBu\", \"labelMargin\": 20}),\n document.getElementById('iK03CNT5FAAORERKF9L5H')\n );\n</script>",
"text/plain": "<shap.plots._force.AdditiveForceVisualizer at 0x7f3a4daa5dd0>"
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind = 2\n",
"shap.plots.force(shap_values[ind])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Positive Review:\n",
"I finally saw this film tonight after renting it at Blockbuster (VHS). I have to agree that it is wildly original. Yes, maybe the characters were not fully realized but it isn't one of those movies. Rather, we are treated to the director's eye, his vision of what the story is about. And it does not stop. And to be honest, I didn't want it to. I do believe that Sabu had to have influenced the director's of 'Lock, Stock & Two Smoking Barrels' and 'Run, Lola, Run'. But I absolutely loved the way the three leads SEE the beautiful woman on the street to distract them momentarily. I really need to see this director's other work because this film really intrigued me. If you want insight, culture, sturm und drang, go somewhere else. If you want a laugh, camera movement and criminal hilarity, look here.\n",
"\n"
]
}
],
"source": [
"print(\"Positive\" if y_test[ind] else \"Negative\", \"Review:\")\n",
"print(corpus_test[ind])"
]
}
],
"metadata": {
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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