UW Implement a TextClassifier Data Type & Binary Decision Tree Programming Exercise

Question Description

I’m working on a java project and need support to help me learn.

Below I have attached the workspace as well as the full spec, please implement the methods below according to the spec

Only 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 splitter

2) 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 subtrees majority label. For example, pruning the above decision tree to depth 1 would result in the following structure.

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