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This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
This repository contains files and information about step 1 of Kaphta Architecture: Text classification of PubMed abstracts on anticancer activity, using the R language.
Simulate one case of customer churn where we work on a data of postpaid customers with a contract. Predict whether a customer will cancel their service in the future or not.
Development of Predictive Model for the Classification of Genes Associated with Abiotic Stress-Resistant Traits in Rice using Supervised Machine Learning
Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it allows retailers to identify relationships between the items that people buy.
Bi and Big Data Analytics, sparkR, Supervised and Unsupervised Machine Learning techniques The project's aim is of applying a supervised and an unsupervised machine learning technique on a dataset to test different models/scenario, interpret the results, perform predictions for each model and visualised the results.