This is an attempt to summarize feature engineering methods that I have learned over the course of my graduate school.

Toolkit for Doing Research with ECMAScript-based Statistics (DRESS Kit)

A wrapper containing search algorithm of Forward Selection + Pattern Classifier of KNN to use optimal features in prostate cancer

A MatLab package for System Identification using linear and nonlinear auto-regresive models (N)AR, (N)ARX and (N)ARMAX models

data visualization/analysis of video game sales

Project ini bertujuan untuk membandingkan algoritma SVM sebelum dan sesudah dilakukan forward selection sebagai seleksi fitur untuk memprediksi kualitas air. Dataset yang digunakan berasal dari kaggle, Pada dataset tersebut terdapat 10 atribut yang terdiri dari 9 atribut ciri dan 1 atribut label, 9 atribut bebas diantaranya ph, hardness, solids,…

workspace for feature/model selection on different projects

Classification with Feature Selection and Extraction Methods

Year after year the percentage of carbon dioxide emissions in Jordan increase dramatically, and this lead to increase the temperature , to investigate this, the project aims to study the impact of CO2 emissions in on temperature and then use deep learning algorithm to predict the CO2 emission level through the next 10 years

Forward stagewise sparse regression estimation implemented for gretl.

Used CDC dataset for heart attack detection in patients. Balanced the dataset using SMOTE and Borderline SMOTE and used feature selection and machine learning to create different models and compared them based on metrics such as F-1 score, ROC AUC, MCC, and accuracy.

A classification project.

a short assignment on classification of small dataset.

Factors that affect manufacturing GDP SA perspective

Code templates for different ML algorithms

A report of Landing.Jobs Data Challenge with a purpose: to show that if you are a woman, you are in disadvantage and the urge for a change!

Statistical Modelling of Swine Flu Outbreak Data

Ejercicio de regresiones por distintos métodos (Mejor Selección de Conjuntos, Selección de pasos hacia adelante, Ridge, LASSO, Elastic Net, Componentes Principales, Mínimos Cuadrados Parciales, etc.)

Answer to how to select variables in data set and build simpler, faster, more reliable and interpretable ML models

A Python implementation of feature selection algorithms using k-Nearest Neighbor classification. This project implements three different search strategies for finding optimal feature subsets: Forward Selection, Backward Elimination, and Simulated Annealing.