Kaggle Competition using 15 numerical predictors to predict a continuous outcome.

Overview

Kaggle-Comp.-Data-Mining

Kaggle Competition using 15 numerical predictors to predict a continuous outcome as part of a final project for a stats data mining course. I later went back and extended work to include more models/attempts.

Machine Learning Models attempted for predictions:

  • Simple Multiple Linear Regression
  • Polynomial Regression
  • Ridge and Lasso Regression
  • Principal Component Regression
  • Support Vector Classifiers and Support Vector Machines
  • Deep and Prunned Regression Trees
  • Bagging and Boosting
  • Random Forests (Best Model for Predictions)
  • Artificial Neural Networks for Regression

Kaggle Competition Link:

https://www.kaggle.com/c/ucla-stats-101c-2021-lec3-new/overview

Owner
moisey alaev
I am currently a UCLA Senior studying Math of Computation and Minoring in Stats. I am most passionate about Machine Learning and Software Development.
moisey alaev
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
A simple python program which predicts the success of a movie based on it's type, actor, actress and director

Movie-Success-Prediction A simple python program which predicts the success of a movie based on it's type, actor, actress and director. The program us

Mahalinga Prasad R N 1 Dec 17, 2021
Python/Sage Tool for deriving Scattering Matrices for WDF R-Adaptors

R-Solver A Python tools for deriving R-Type adaptors for Wave Digital Filters. This code is not quite production-ready. If you are interested in contr

8 Sep 19, 2022
Simple linear model implementations from scratch.

Hand Crafted Models Simple linear model implementations from scratch. Table of contents Overview Project Structure Getting started Citing this project

Jonathan Sadighian 2 Sep 13, 2021
Implementation of the Object Relation Transformer for Image Captioning

Object Relation Transformer This is a PyTorch implementation of the Object Relation Transformer published in NeurIPS 2019. You can find the paper here

Yahoo 158 Dec 24, 2022
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python

BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor

Jared M. Smith 40 Aug 26, 2022
MiniTorch - a diy teaching library for machine learning engineers

This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses

1.1k Jan 07, 2023
Stock Price Prediction Bank Jago Using Facebook Prophet Machine Learning & Python

Stock Price Prediction Bank Jago Using Facebook Prophet Machine Learning & Python Overview Bank Jago has attracted investors' attention since the end

Najibulloh Asror 3 Feb 10, 2022
This repository contains full machine learning pipeline of the Zillow Houses competition on Kaggle platform.

Zillow-Houses This repository contains full machine learning pipeline of the Zillow Houses competition on Kaggle platform. Pipeline is consists of 10

2 Jan 09, 2022
Combines Bayesian analyses from many datasets.

PosteriorStacker Combines Bayesian analyses from many datasets. Introduction Method Tutorial Output plot and files Introduction Fitting a model to a d

Johannes Buchner 19 Feb 13, 2022
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.

Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning

Microsoft 149 Jan 06, 2023
A library to generate synthetic time series data by easy-to-use factors and generator

timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge

Nike Inc. 87 Dec 20, 2022
A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al.

pyUpSet A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al. Contents Purpose How to install How it work

288 Jan 04, 2023
This is the material used in my free Persian course: Machine Learning with Python

This is the material used in my free Persian course: Machine Learning with Python

Yara Mohamadi 4 Aug 07, 2022
Interactive Parallel Computing in Python

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

IPython 2.3k Dec 30, 2022
A machine learning toolkit dedicated to time-series data

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

2.3k Jan 05, 2023
AutoOED: Automated Optimal Experiment Design Platform

AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems an

Yunsheng Tian 107 Jan 03, 2023
Extended Isolation Forest for Anomaly Detection

Table of contents Extended Isolation Forest Summary Motivation Isolation Forest Extension The Code Installation Requirements Use Citation Releases Ext

Sahand Hariri 377 Dec 18, 2022
slim-python is a package to learn customized scoring systems for decision-making problems.

slim-python is a package to learn customized scoring systems for decision-making problems. These are simple decision aids that let users make yes-no p

Berk Ustun 37 Nov 02, 2022
CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

ZhihuiYangCS 8 Jun 07, 2022