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Implementation of Decision Tree algorithm to classify the personalities of the people. Data used was the combination of data from Big Five personality test and 16 personality test.

A Natural Language Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like multinomial-naive-bayes,logistic regression,svm,decision trees to compare accuracy and using various data cleaning and processing techniques like PorterStemmer,CountVectorizer,TFIDF ... Read more

Random Forest (Decision Tree) implementation in Swift

With WWW being the global platform, various fields inclusive to the same have emerged until hitherto. Due to ever-changing forms of cyber Security, it has become a necessity to classify Malicious websites so as to secure personal content. In this project we have implemented The State-Of-the-Art... Read more

C4.5 is a commonly used in decision tree algorithm in data mining for classification. The existing C4.5 algorithm implementation is running in serial way. We are implementing this algorithm using Hadoop MapReduce framework which can run parallel in multiple system.

Machine learning is changing the world and if you want to be a part of the ML revolution, this is a great place to start! This repository serves as an excellent introduction to implementing machine learning algorithms in depth such as linear and logistic regression, decision tree, random forest, ... Read more

This project is on twitter sentimental analysis by combining lexicon based and machine learning approaches. A supervised lexicon-based approach for extracting sentiments from tweets was implemented. Various supervised machine learning approaches were tested using scikit-learn libraries in python ... Read more

This repository is mainly combined with OpenCV4 (C++ version) to implement some basic image processing operations, classical machine learning algorithms (such as K-Means, KNN, SVM, decision trees, Bayesian classifiers, etc.), and common deep learning algorithms.

Implementation of Decision Tree Classifier, Esemble Learning, Association Rule Mining and Clustering models(Kmodes & Kprototypes) for Customer attrition analysis of telecommunication company to identify the cause and conditions of the churn.

This repository contains R implementations of classification models including KNN, Logistic Regression, Decision Trees, and Naive Bayes. It explores the impact of Principal Component Analysis (PCA) on model performance using simulated data, comparing accuracy, sensitivity, specificity, and kappa ... Read more