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…

Cell type pipes for R

Cell signatures, with confidence.

R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.

Implementation of k-Nearest Neighbours algorithm for use on geometric morphometric data and a simulated dataset.

The FOTO (Fourier Transform Textural Ordination) R package.

Predict, Your Loan is approved & not. we use R and ML for prediction.

The objective of this work is to provide tools to be used for the classification of ordinal categorical distributions. To demonstrate how to do it, we propose an Homogeneity (HI) and Location (LI) Index to measure the concentration and central value of an ordinal categorical distribution.

Streaming Maximum Likelihood Estimation

OptimClassifier — Create the Best Train for Classification Models

Predicting the churn of customers in a Telecom company using classification algorithms.

🌳 Predicting a wildfire's severity using classification models

As part of this project, I have developed algorithms from scratch using Gradient Descent method. The first algorithm developed will be used to predict the average GPU Run Time and the second algorithm will be used to classify a GPU run process as high or low time consuming process.

Fire Incident risk classification Data Mining project

Imagine you are the front runner for democratic party primaries in 2008 - 1 week into elections you have won a few states(Obama) and your opponent (Hillary) is catching up. How you can use analytics to predict which of the remaining seats will you win using demographic data from states you won and lost. Can we accurately classify win or lose for…

Data Mining Project: Classification of the Car Evaluation Dataset.

Implementation of unsupervised and supervised algorithms.

1. Algoritmos de clasificación de operaciones financieras / 2. Liquidez (horquillas y profundidad) / 3. Descomposición de horquillas / 4. Modelos basados en series temporales

Mushrooms Classification with R. Machine Learning - decision tree and SVM.