Predicting diabetes over a five year period using logistic regression and the Pima First-Nation dataset

Overview

Diabetes

This script uses the Pima First Nations dataset to create a model to predict whether or not an individual will develop Diabetes Mellitus Type 2 within a five year time span

This is a quick little project involving regression analysis and diabetes. I have created this project to better my understanding of not only the content currently being covered in my anatomy and physiology course, but also to practice working with simple regression models and common libraries.

So far, this model is able to predict values with a ~75% accuracy (not bad given the lack of data and size of the model, but not great). There are several ways to optimize this model. A few I can think of off the top of my head would be gathering more data to train it on, and cleaning the data in a different way (ie... not replacing 0 values with the mean value of that column).

Dataset found on kaggle: https://www.kaggle.com/kumargh/pimaindiansdiabetescsv

Python module for performing linear regression for data with measurement errors and intrinsic scatter

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

Rodrigo Nemmen 56 Sep 27, 2022
🔬 A curated list of awesome machine learning strategies & tools in financial market.

🔬 A curated list of awesome machine learning strategies & tools in financial market.

GeorgeZou 1.6k Dec 30, 2022
An open-source library of algorithms to analyse time series in GPU and CPU.

An open-source library of algorithms to analyse time series in GPU and CPU.

Shapelets 216 Dec 30, 2022
XManager: A framework for managing machine learning experiments 🧑‍🔬

XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction

DeepMind 620 Dec 27, 2022
Implementation of deep learning models for time series in PyTorch.

List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Yunkai Zhang 275 Dec 28, 2022
A collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Chris Santiago 0 Mar 30, 2022
Python bindings for MPI

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

MPI for Python 604 Dec 29, 2022
Magenta: Music and Art Generation with Machine Intelligence

Magenta is a research project exploring the role of machine learning in the process of creating art and music. Primarily this involves developing new

Magenta 18.1k Dec 30, 2022
onelearn: Online learning in Python

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

15 Nov 06, 2022
Distributed Deep learning with Keras & Spark

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Max Pumperla 1.6k Dec 29, 2022
Dual Adaptive Sampling for Machine Learning Interatomic potential.

DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong

6 Jul 06, 2022
The Fuzzy Labs guide to the universe of open source MLOps

Open Source MLOps This is the Fuzzy Labs guide to the universe of free and open source MLOps tools. Contents What is MLOps, anyway? Data version contr

Fuzzy Labs 352 Dec 29, 2022
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

3 Apr 10, 2022
Machine Learning toolbox for Humans

Reproducible Experiment Platform (REP) REP is ipython-based environment for conducting data-driven research in a consistent and reproducible way. Main

Yandex 663 Dec 31, 2022
Automated Time Series Forecasting

AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod

Colin Catlin 652 Jan 03, 2023
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

DataCanvas 216 Dec 23, 2022
Hierarchical Time Series Forecasting using Prophet

htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th

Collin Rooney 131 Dec 02, 2022
pymc-learn: Practical Probabilistic Machine Learning in Python

pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-

pymc-learn 196 Dec 07, 2022
A machine learning web application for binary classification using streamlit

Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas

abdelhak mokri 1 Dec 20, 2021
Deploy AutoML as a service using Flask

AutoML Service Deploy automated machine learning (AutoML) as a service using Flask, for both pipeline training and pipeline serving. The framework imp

Chris Rawles 221 Nov 04, 2022