Allows columns to be dropped from a feature vector based on properties of the metadata about what is contained in each column (will work only on vectors) created with OpVectorMetadata
function that goes from OpVectorColumnMetadata to boolean for dropping columns (cases that evaluate to true will be dropped)
new Vector with columns removed by function
Apply inverse-document frequency transformation.
minimum number of documents in which a term should appear for filtering (default: 0)
Apply Latent Dirichlet Allocation to compute topic distributions
num of iterations between two consecutive checkpoints, -1 means disabled
number of topics (clusters) to infer
maximum number of iterations
optimizer or inference algorithm used to estimate the LDA model, "online" or "em"
fraction of the corpus to be sampled and used in mini-batch gradient descent
Apply Random Forest classifier