Below I have attached the workspace as well as the full specOnly the following 4 methods need to be implemented in TextClassifier.java:1) TextClassifier(Vectorizer vectorizer, Splitter splitter)Constructs a new TextClassifier given a fitted vectorizer for transforming data points and a splitter for determining the splits in the treeTextClassifier(Vectorizer vectorizer, Splitter splitter2) boolean classify(String text)Returns a boolean representing the predicted label for the given text.3) void print()Prints a Java code representation of this decision tree in if/else statement format without braces and with 1 additional indentation space per level in the decision tree. Leaf nodes should print “return true;” or “return false;” depending on the label value.4) void prune(int depth)Prunes this tree to the given depth. Each pruned subtree is replaced with a new node representing the subtree’s majority label. For example, pruning the above decision tree to depth 1 would result in the following structure.Specification
Implement a TextClassifier data type, a binary decision tree for classifying text documents.
1) TextClassifier(Vectorizer vectorizer, Splitter splitter)
Constructs a new TextClassifier given a fitted vectorizer for transforming data points
and a splitter for determining the splits in the tree.
boolean classify(String text)
Returns a boolean representing the predicted label for the given text.
2) void print()
Prints a Java code representation of this decision tree in if/else statement format
without braces and with 1 additional indentation space per level in the decision
tree. Leaf nodes should print “return true;” or “return false;” depending on the
label value.
if (vector[318]
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