water.bindings.pojos.Word2VecParametersV3 Maven / Gradle / Ivy
package water.bindings.pojos;
import com.google.gson.Gson;
public class Word2VecParametersV3 extends ModelParametersSchema {
/** Set size of word vectors */
public int vecSize;
/** Set max skip length between words */
public int windowSize;
/** Set threshold for occurrence of words. Those that appear with higher frequency in the training data
will be randomly down-sampled; useful range is (0, 1e-5) */
public float sentSampleRate;
/** Use Hierarchical Softmax or Negative Sampling */
public NormModel normModel;
/** Number of negative examples, common values are 3 - 10 (0 = not used) */
public int negSampleCnt;
/** Number of training iterations to run */
public int epochs;
/** This will discard words that appear less than times */
public int minWordFreq;
/** Set the starting learning rate */
public float initLearningRate;
/** Use the continuous bag of words model or the Skip-Gram model */
public WordModel wordModel;
/* INHERITED: Destination id for this model; auto-generated if not specified
* public ModelKeyV3 model_id;
*/
/* INHERITED: Training frame
* public FrameKeyV3 training_frame;
*/
/* INHERITED: Validation frame
* public FrameKeyV3 validation_frame;
*/
/* INHERITED: Number of folds for N-fold cross-validation
* public int nfolds;
*/
/* INHERITED: Keep cross-validation model predictions
* public boolean keep_cross_validation_predictions;
*/
/* INHERITED: Keep cross-validation fold assignment
* public boolean keep_cross_validation_fold_assignment;
*/
/* INHERITED: Allow parallel training of cross-validation models
* public boolean parallelize_cross_validation;
*/
/* INHERITED: Response column
* public ColSpecifierV3 response_column;
*/
/* INHERITED: Column with observation weights
* public ColSpecifierV3 weights_column;
*/
/* INHERITED: Offset column
* public ColSpecifierV3 offset_column;
*/
/* INHERITED: Column with cross-validation fold index assignment per observation
* public ColSpecifierV3 fold_column;
*/
/* INHERITED: Cross-validation fold assignment scheme, if fold_column is not specified
* public FoldAssignmentScheme fold_assignment;
*/
/* INHERITED: Ignored columns
* public String[] ignored_columns;
*/
/* INHERITED: Ignore constant columns
* public boolean ignore_const_cols;
*/
/* INHERITED: Whether to score during each iteration of model training
* public boolean score_each_iteration;
*/
/* INHERITED: Model checkpoint to resume training with
* public ModelKeyV3 checkpoint;
*/
/* INHERITED: Early stopping based on convergence of stopping_metric. Stop if simple moving average of length k of the stopping_metric does not improve for k:=stopping_rounds scoring events (0 to disable)
* public int stopping_rounds;
*/
/* INHERITED: Maximum allowed runtime in seconds for model training. Use 0 to disable.
* public double max_runtime_secs;
*/
/* INHERITED: Metric to use for early stopping (AUTO: logloss for classification, deviance for regression)
* public StoppingMetric stopping_metric;
*/
/* INHERITED: Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much)
* public double stopping_tolerance;
*/
/** Return the contents of this object as a JSON String. */
@Override
public String toString() {
return new Gson().toJson(this);
}
}