hana_ml.text.tm package

This module provides various functions of text mining. The following functions are available:

• tf_analysis()

• text_classification()

• get_related_doc()

• get_related_term()

• get_relevant_doc()

• get_relevant_term()

• get_suggested_term()

• TFIDF

• TextClassificationWithModel

hana_ml.text.tm

tf_analysis(data[, lang, enable_stopwords, ...])	Perform Term Frequency(TF) analysis on the given document.
text_classification(pred_data[, ref_data, ...])	This function classifies (categorizes) an input document with respect to sets of categories (taxonomies) using TF-IDF text vectorizer and KNN classifier.
get_related_doc(pred_data[, ref_data, top, ...])	This function returns the top-ranked related documents for a query document / or multiple docments based on Term Frequency - Inverse Document Frequency (TF-IDF) result or reference data.
get_related_term(pred_data[, ref_data, top, ...])	This function returns the top-ranked related terms for a query term / or multiple terms based on Term Frequency - Inverse Document Frequency (TF-IDF) result or reference data.
get_relevant_doc(pred_data[, ref_data, top, ...])	This function returns the top-ranked documents that are relevant to a term / or multiple terms based on Term Frequency - Inverse Document Frequency (TF-IDF) result or reference data.
get_relevant_term(pred_data[, ref_data, ...])	This function returns the top-ranked relevant terms that describe a document / or multiple docments based on Term Frequency - Inverse Document Frequency (TF-IDF) result or reference data.
get_suggested_term(pred_data[, ref_data, ...])	This function returns the top-ranked terms that match an initial substring / or multiple substrings based on Term Frequency - Inverse Document Frequency (TF-IDF) result or reference data.

TFIDF()	Class for term frequency–inverse document frequency.
TextClassificationWithModel([language, ...])	Text classification class.