|
Class Summary |
| Binarizer |
:: Experimental ::
Binarize a column of continuous features given a threshold. |
| Bucketizer |
:: Experimental ::
Bucketizer maps a column of continuous features to a column of feature buckets. |
| ElementwiseProduct |
:: Experimental ::
Outputs the Hadamard product (i.e., the element-wise product) of each input vector with a
provided "weight" vector. |
| HashingTF |
:: Experimental ::
Maps a sequence of terms to their term frequencies using the hashing trick. |
| IDF |
:: Experimental ::
Compute the Inverse Document Frequency (IDF) given a collection of documents. |
| IDFModel |
|
| Normalizer |
:: Experimental ::
Normalize a vector to have unit norm using the given p-norm. |
| OneHotEncoder |
:: Experimental ::
A one-hot encoder that maps a column of category indices to a column of binary vectors, with
at most a single one-value per row that indicates the input category index. |
| PolynomialExpansion |
:: Experimental ::
Perform feature expansion in a polynomial space. |
| RegexTokenizer |
:: Experimental ::
A regex based tokenizer that extracts tokens either by using the provided regex pattern to split
the text (default) or repeatedly matching the regex (if gaps is true). |
| StandardScaler |
:: Experimental ::
Standardizes features by removing the mean and scaling to unit variance using column summary
statistics on the samples in the training set. |
| StandardScalerModel |
|
| StringIndexer |
:: Experimental ::
A label indexer that maps a string column of labels to an ML column of label indices. |
| StringIndexerModel |
:: Experimental ::
Model fitted by StringIndexer. |
| Tokenizer |
:: Experimental ::
A tokenizer that converts the input string to lowercase and then splits it by white spaces. |
| VectorAssembler |
:: Experimental ::
A feature transformer that merges multiple columns into a vector column. |
| VectorIndexer |
:: Experimental ::
Class for indexing categorical feature columns in a dataset of Vector. |
| VectorIndexer.CategoryStats |
Helper class for tracking unique values for each feature. |
| VectorIndexerModel |
:: Experimental ::
Transform categorical features to use 0-based indices instead of their original values. |
| Word2Vec |
:: Experimental ::
Word2Vec trains a model of Map(String, Vector), i.e. |
| Word2VecModel |
:: Experimental ::
Model fitted by Word2Vec. |