sagarwhu Goto Github PK

artifact-evaluation

awesome-msr

A curated repository of software engineering repository mining data sets

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bellwether

Simpler Transfer Learning (Using "Bellwethers"). ARXIV link: https://arxiv.org/abs/1703.06218

books

Free Ebooks

buglocalization-dataset

cityu-latex-ppt

Cityu LaTeX Presentation

cityu-thesis

A collection of LaTeX thesis template for students at City University of Hong Kong.

cleanthesis-cityu

Yet another XeLaTeX thesis template for MPhil, PhD and PD students at City University of Hong Kong.

concept-drift

Algorithms for detecting changes from a data stream.

concept-drift-report

conceptdriftgenerator

Generator for classification with concept drift

crosspare

Cross-project defection prediction tooling

dataminingguidebook-codes

《面向程序员的数据挖掘指南》源码

defectdata

An R package of Defect Prediction Datasets for Software Engineering Research

docker

Docker - the open-source application container engine

empiricalstandards

Empirical standards for conducting and evaluating research in software engineering

ensemble-methods-using-r

I have done my individual project (dissertation) on ensemble methods. In which I first did the background study on different ensemble methods and then implemented Boosting, AdaBoost, Bagging and random forest techniques on underlying machine learning algorithms. I used boosting method to boost the performance of weak learner like decision stumps. Implemented bagging for decision trees (both regression and classification problems) and for KNN classifier. Used random forest for classification trees. I have implemented a special algorithm of boosting called “AdaBoost” on logistic regression algorithm using different threshold values. Then plotted the different graphs like an error rate as a function of boosting, bagging and random forest iterations. Compared results of bagging with boosting. Analysed the performance of classifier before applying ensemble methods and after applying ensemble methods. Used different model evaluation techniques like cross-validation, MSE, PRSS, ROC curves, confusion matrix, and out-of-bag error estimation to estimate the performance of ensemble techniques.

far

free-algorithm-books-1

free-programming-books

:books: Freely available programming books

ggplot2

An implementation of the Grammar of Graphics in R

githubarchive.org

GitHub Archive is a project to record the public GitHub timeline, archive it, and make it easily accessible for further analysis.

gitstudy

grokking_algorithms

Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)

hugo-academic

The personal website framework for Hugo

interpretability-heart

interpretable-ml-book

Book about interpretable machine learning

jgov

kme

dataset description