rasbt--python-machine-learning-book
wehub-resource-sync
21 行
700 B
Markdown
21 行
700 B
Markdown
Sebastian Raschka, 2015
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Python Machine Learning - Code Examples
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## Chapter 4 - Building Good Training Sets – Data Preprocessing
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- 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 |