Final project for the subject Data Mining I of my MsC.

Data Science in R (multiple algo`s)

Classify the subsidy eligible users based on their electricity usage patterns

Worked on building a predictive model by considering multicollinearity and other Machine learning concepts related to  factors or variables using R programming. 

K-means clustering algorithm to group people who live close to each other.

A comparison of centroid-based, density-based and hierarchical clustering algorithms

The repository contains some of the work done by me and 4 colleagues for a university project of the "data analysis for business" class. The project aims at identifying the best deals and strategies to take by rental agencies to maximise profits in the Brazilian House Market. On the other hand, We also analyzed good deals for mid-income households.

Examples of some popular algorthms for solving problems in maschine learning

Implement Decision Tree and KMeans using R

Supervised and unsupervised analysis

KNN (K nearest neighbors) and KMeans clustering implementation using the infamous iris dataset using the R language

Here are some of the algorithms for machine learning mostly clustering.....

K-means as an unsupervised machine learning technique. Customer Segmentation Case.

Machine Learning algorithms from scratch in R; Spring 2018 - Stockton University; K Means, Perceptron, Linear Regression

e-commerce data is analyzed to identify the most valuable customers, regions and shopping habits. KMeans clustering is used to nail down the optimal clustering model. Shopping transactions are significantly different by days of a week based on non-normal distributions.

Auto market segments identification with K-means

Predicting imdb score using data-science algorithems

A project experimenting with implementing clustering algorithms in R

Algorithms for computing cluster validity indices including a new correlation-based called Wiroonsri index