train-test-split
There are 0 repository under train-test-split topic.
graph-part / graph-part
GraphPart, a data partitioning method for ML on biological sequences
Language:Jupyter Notebook 20ODAncona / bboxconverter
This library allows reading and converting bounding box annotations in many popular formats
Language:Python 18bharatadk / python_splitter
📁 Repo for python_splitter Python package. This package can split Images into Train, Test, Validation folders automatically by shuffling media/images for machine learning.
Language:Python 13yu9824 / kennard_stone
This is an algorithm for evenly partitioning.
Language:Python 10JaanviG / Prediction-using-Decision-Tree-Algorithm
To create a Decision Tree classifier and visualize it graphically, the purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
Language:Jupyter Notebook 3sanketmaneDS / Logistic_Regression
This repository contains introductory notebook for logistic regression
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vaitybharati / P36.-Supervised-ML---Decision-Tree---C5.0-Entropy-Iris-Flower-
Supervised-ML-Decision-Tree-C5.0-Entropy-Iris-Flower-Using Entropy Criteria - Classification Model. Import Libraries and data set, EDA, Apply Label Encoding, Model Building - Building/Training Decision Tree Classifier (C5.0) using Entropy Criteria. Validation and Testing Decision Tree Classifier (C5.0) Model
Language:Jupyter Notebook 3Ava33343 / Soft_or_Hard_Bank
Time series analysis on Yen Futures with ACF, PACF, ADF tests and seasonal decomposition to detect stationary trends. Screen for robust regression models on rolling train-test windows.
Language:Jupyter Notebook 2Best-Brain-Gang / roboadvisor-diversification
This creates an AWS Chatbot to give users their investment portfolio based on their risk tolerance level i.e. conservative, moderate, or aggressive. With the use of machine learning, the tool will be created to different portfolios based off that.
Language:Jupyter Notebook 2marmurar / jano
A time slicer for training and testing temporally correlated Machine Learning models.
Language:Python 2NeonOstrich / Credit-Risk-Classification-using-Logistic-Regression
Trained and evaluated two supervised machine learning models using original and resampled data to identify 'healthy loan' and 'high risk loan' applicants from financial disclosures.
Language:Jupyter Notebook 2QuantumMonkey / LP-Diabetes-Prediction
Learning Project ML - Diabetes Prediction
Language:Jupyter Notebook 2aarryasutar / Linear_Multivariate_Regression_on_Football_Statistics
Linear regression models are used to predict football player attacking stats based on attributes like finishing and passing, with the model trained, evaluated, and applied for predictions. Multiple features improve accuracy, and performance is assessed using metrics like MSE and R-squared.
Language:Jupyter Notebook 1Abhik35 / Assignment-SVM-forestfires
classify the Size_Categorie using SVM
Language:Jupyter Notebook 1adil-imran / Customer-Retention-Deep-Learning
Customer Retention Deep Learning Model
Language:Jupyter Notebook 1aditijoshi613 / Image-Classification
Classification model to categorize clothing items into distinct classes
Language:Jupyter Notebook 1AloRay / CREDIT-RISK-PREDICTION
Model selection crucial in loan approval prediction project. Random Forest outperformed Logistic Regression, emphasizing importance of choosing appropriate models for accurate predictions.
Language:Jupyter Notebook 1BradyFisher / Housing-Prices-Machine-Learning-Project
This is a project where I use the Random Forest Regression and XGBoost Machine Learning Techniques to held predict the Sales Price of Houses..
Language:Jupyter Notebook 1This is a project where use the Random Forest Classifier and XGBoost Machine Learning Techniques to held predict what passengers survived the sinking of the Titanic.
Language:Jupyter Notebook 1chinmayeeguru / Bike-Sharing-Linear-Regression-Model
To model the demand for shared bikes with the available independent variables
Language:Jupyter Notebook 1Eben2020-hp / Train-Test-Split-using-R
Understanding Train-Test-Split in R
Language:R 1elifftosunn / Bert-Bank-Model
It is a Turkish BERT-based model that will analyze people's bank complaints and classify them according to one of eight categories.
Language:Jupyter Notebook 1iamkirankumaryadav / Algorithms
Machine Learning with Scikit Learn
Language:Jupyter Notebook 1jagadeeshpj / Predicting-The-Energy-Output-Of-Wind-Turbine-Based-On-Weather-Condition
Predicting The Energy Output Of Wind Turbine Based On Weather Condition DEMO LINK : https://youtu.be/ICfu49Ud2HU
Language:HTML 1jesussantana / SkLearn-Train-Test
Scientific programming through the SKLearn / Scikitlearn library
Language:Jupyter Notebook 1jigarpatel108 / Machine-Learning-in-Python-365-Data-Science
Repository of all exercises and assignments in 365 Data Science Machine Learning Course
Language:Jupyter Notebook 1MahtabEK / A-Data-Scientist-for-a-Professional-Football-Club
In this project, you work as a Data Scientist for a professional football club. The owner of the team is very interested in seeing how the use of data can help improve the team's performance, and perhaps win them a championship! The draft is coming up soon (that's when you get to pick new players for your team), and the owner wants you to create a model to help score potential draftees. The model will look at attributes about the player and predict what their "rating" will be once they start playing professionally. The football club's data team has provided the data for 17,993 footballers from the league. Our job is to build a model or model, perform model selection, and make predictions on players you have not yet seen.
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MehmetOKUYAR / Train_Test_Split_txt
You can separate the images in your file as a train test txt file in the yolo format.
Language:Python 1MoinDalvs / Model_Validation_Techniques
1. train_test_split 2.K_fold 3.LeaveoneOut 4.Cross Validation Score 5.Logistic Regression
Language:Jupyter Notebook 1rishabh1882 / Insurance-Prediction-Model
A GitHub repository hosting an insurance prediction model employing Decision Tree, Random Forest, and KNN algorithms, with KNN achieving the highest accuracy score of 87.7% and tested for response on unseen data.
Language:Jupyter Notebook 1shayleaschreurs / Deep_Neural_Networks
Module 13 - I am creating a binary classification model using a deep neural network by preprocessing data for a neural network model , using the model-fit-predict pattern to compile and evaluate a binary classification model , and optimize the model.
Language:Jupyter Notebook 1Thakursiddhesh / Regression-Model-to-Predict-Cement-Compressive-Strength
Different modeling techniques like multiple linear regression and random forest, etc. will be used for predicting the cement compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy.
Language:Jupyter Notebook 1V0xP0p / GroupSplit
GroupSplit is a module to help split datasets into train and test sets for data science and machine learning projects.
Language:Python 1Model-Validation-Methods
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