A simple example of ML classification, cross validation, and visualization of feature importances

Last update: Aug 25, 2022

Related tags

Overview

Simple-Classifier

This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example assumes the use of a retail customer dataset where the user is targeting a binary variable for sale/no sale. I highly recommend running this in Jupyter Notebook or Lab, or potentially in Colab.

Some code was borrowed, with love, from the notebooks of the Kaggle community.

Note that at the time of this publishing, certain libraries used within are not available for Macs running the new M1 silicone processor.

You might also like...

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

6.9k Jan 5, 2023

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

14.5k Jan 7, 2023

machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service

This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.

73 Dec 1, 2022

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

2 Nov 18, 2021

Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

1 Jan 31, 2022

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth

5 Dec 6, 2022

A scikit-learn based module for multi-label et. al. classification

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

802 Jan 1, 2023

Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

84 Nov 25, 2022

A Python package for time series classification

pyts: a Python package for time series classification pyts is a Python package for time series classification. It aims to make time series classificat

1.4k Jan 1, 2023

Owner

Rob

Business analytics, data science and web crawling aficionado.

GitHub

Evidently helps analyze machine learning models during validation or production monitoring

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.

3.1k Jan 7, 2023

A project based example of Data pipelines, ML workflow management, API endpoints and Monitoring.

MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.

33 Dec 3, 2022

K-Means clusternig example with Python and Scikit-learn

Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se

1 Dec 13, 2021

Polyglot Machine Learning example for scraping similar news articles.

Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w

15 Mar 28, 2022

End to End toy example of MLOps

churn_model MLOps Toy Example End to End You might find below links useful Connect VSCode to Git MLFlow Port Heroku App Project Organization ├── LICEN

6 Feb 6, 2022

Houseprices - Predict sales prices and practice feature engineering, RFs, and gradient boosting

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

1 Jan 1, 2022

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

2.4k Jan 2, 2023

A data preprocessing and feature engineering script for a machine learning pipeline is prepared.

FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is

7 Dec 18, 2021

Regularization and Feature Selection in Least Squares Temporal Difference Learning

Regularization and Feature Selection in Least Squares Temporal Difference Learning Description This is Python implementations of Least Angle Regressio

0 Jan 18, 2022

flexible time-series processing & feature extraction

tsflex is a toolkit for flexible time-series processing & feature extraction, making few assumptions about input data. Useful links Documentation Exam

206 Dec 28, 2022