wehub-resource-sync
16 lines
538 B
TeX
16 lines
538 B
TeX
Dealing with missing data
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Eliminating samples or features with missing values
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Imputing missing values
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Understanding the scikit-learn estimator API
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Handling categorical data
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Mapping ordinal features
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Encoding class labels
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Performing one-hot encoding on nominal features
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Partitioning a dataset in training and test sets
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Bringing features onto the same scale
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Selecting meaningful features
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Sparse solutions with L1 regularization
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Sequential feature selection algorithms
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Assessing feature importance with random forests
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Summary
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