Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news articl…

This Repository Contains R-Codes executed on various Datasets in RStudio. I Hope This Repository is very helpful for those who are Willing to build their Career in Data Science, Big Data.

Pixel based classification of satellite imagery - feature generation using Orfeo Toolbox, feature selection using Learning Vector Quantization, CLassification using Decision Tree, Neural Networks, Random Forests, KNN and Naive Bayes Classifier

Various Classification models used are Logistic regression, K-NN, Support Vector Machine, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification using R

Exercises From Book "Applied Predictive Modeling" by "Kuhn and Johnson (2013)"

A tidy implementation of the Naive Bayes classifier

Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning

The program is written in R which analysis patient's health condition using sentiment analysis and classifies as exist, deteriorate and recover using machine learning algorithm - Naive bayes

Analyze NASDAQ100 stock data. Used ARIMA + GARCH model and machine learning techniques Naive Bayes and Decision tree to determine if we go long or short for a given stock on a particular day

This repository contains coursework for the Data Mining course in the MS Applied Business Analytics program at Boston University.

The objective of the project was to build a model that can accurately differentiate spam messages from ham ones. In doing so, I tried to showcase the ability of naive-bayes algorithm to accurately predict the mesage as spam or ham.

Projects who cover topics from text mining up to classification, association, clustering and regression algorithms

Source code and Visualizations

Six machine learning models for predicting bladder cancer progression using Caret package

An R implementation of Naive Bayes model and Neural Network model for the classification of the MNIST dataset.

Prediction whether the economic crisis will occur in Africa countries

NUS CS4220: Building a Weighted Gaussian Naive Bayes Model for prediction of gene essentiality in cancer cell-lines.

USF MATH 373 Case Study 1: Spam Detection with Naive Bayes

Use the publicly available NCDC storm data to analyze it and provide insights.

Code templates for different ML algorithms