| Name | Description | Type | Package | Framework |
| ChiSqSelector | Class | org.apache.spark.mllib.feature | Apache Spark | |
| ChiSqSelectorModel | Chi Squared selector model. | Class | org.apache.spark.mllib.feature | Apache Spark |
| ElementwiseProduct | Outputs the Hadamard product (i. | Class | org.apache.spark.mllib.feature | Apache Spark |
| HashingTF | Maps a sequence of terms to their term frequencies using the hashing trick. | Class | org.apache.spark.mllib.feature | Apache Spark |
| IDF | Inverse document frequency (IDF). | Class | org.apache.spark.mllib.feature | Apache Spark |
| IDF .DocumentFrequencyAggregator | Document frequency aggregator. | Class | org.apache.spark.mllib.feature.IDF | Apache Spark |
| IDFModel | Represents an IDF model that can transform term frequency vectors. | Class | org.apache.spark.mllib.feature | Apache Spark |
| Normalizer | Normalizes samples individually to unit L^p^ norm For any 1 <= p < Double. | Class | org.apache.spark.mllib.feature | Apache Spark |
| PCA | A feature transformer that projects vectors to a low-dimensional space using PCA. | Class | org.apache.spark.mllib.feature | Apache Spark |
| PCAModel | Model fitted by PCA that can project vectors to a low-dimensional space using PCA. | Class | org.apache.spark.mllib.feature | Apache Spark |
| StandardScaler | Standardizes features by removing the mean and scaling to unit std using column summary statistics on the samples in the training set. | Class | org.apache.spark.mllib.feature | Apache Spark |
| StandardScalerModel | Represents a StandardScaler model that can transform vectors. | Class | org.apache.spark.mllib.feature | Apache Spark |
| VectorTransformer | Interface | org.apache.spark.mllib.feature | Apache Spark | |
| VocabWord | Class | org.apache.spark.mllib.feature | Apache Spark | |
| Word2Vec | Class | org.apache.spark.mllib.feature | Apache Spark | |
| Word2VecModel | Class | org.apache.spark.mllib.feature | Apache Spark | |