Enhanced the code and their functionality and works fine

[VishvakR]

We enhanced the project by adding input-based prediction, multi-model machine learning training with evaluation and automatic best-model selection, full model saving and loading capabilities, modularized preprocessing and training pipelines, processed-data saving, and comprehensive visualization features such as correlation heatmaps and interactive menu-based graphs.

[Sushant1-oops]

🤖 AI Code Review

❌ Changes requested — critical issues must be resolved.

PR: Enhanced the code and their functionality and works fine by @VishvakR

Summary

Category	Findings
🔒 Security	0
⚡ Performance	0
✨ Style	0
🧪 Tests	6
Total	6 (3 critical, 1 warnings, 2 suggestions)

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🧪 Tests

🔴 CRITICAL — Missing test cases for Decision Tree and Random Forest Classifiers

File: Project.py | Location: DecisionTreeClassifier() and RandomForestClassifier() usage

The DecisionTreeClassifier() and RandomForestClassifier() are used without any test cases to verify their correctness. This is a critical issue as it may lead to incorrect predictions.

💡 Suggestion: Add test cases to verify the correctness of DecisionTreeClassifier() and RandomForestClassifier().

🔴 CRITICAL — Missing test cases for Linear Model Perceptron and Logistic Regression

File: Project.py | Location: LinearModelPerceptron() and LogisticRegression() usage

The LinearModelPerceptron() and LogisticRegression() are used without any test cases to verify their correctness. This is a critical issue as it may lead to incorrect predictions.

💡 Suggestion: Add test cases to verify the correctness of LinearModelPerceptron() and LogisticRegression().

🔴 CRITICAL — Missing test cases for Neural Network MLP Classifier

File: Project.py | Location: MLPClassifier() usage

The MLPClassifier() is used without any test cases to verify its correctness. This is a critical issue as it may lead to incorrect predictions.

💡 Suggestion: Add test cases to verify the correctness of MLPClassifier().

🟡 WARNING — Missing test cases for user input

File: Project.py | Location: input() usage

The input() function is used to get user input without any test cases to verify its correctness. This is a warning as it may lead to unexpected behavior.

💡 Suggestion: Add test cases to verify the correctness of user input.

🔵 SUGGESTION — Missing test cases for model selection and evaluation

File: Project.py | Location: Model selection and evaluation

The code does not have any test cases to verify the correctness of model selection and evaluation. This is a suggestion as it would be beneficial to have test cases for this.

💡 Suggestion: Add test cases to verify the correctness of model selection and evaluation.

🔵 SUGGESTION — Missing test cases for data preprocessing

File: Project.py | Location: Data preprocessing

The code does not have any test cases to verify the correctness of data preprocessing. This is a suggestion as it would be beneficial to have test cases for this.

💡 Suggestion: Add test cases to verify the correctness of data preprocessing.

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_{🤖 Generated by AI PR Reviewer — Security · Performance · Style · Test Coverage agents powered by Groq + LangGraph}