Topic: train-test-split Goto Github
Some thing interesting about train-test-split
Some thing interesting about train-test-split
train-test-split,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.
User: aarryasutar
train-test-split,classify the Size_Categorie using SVM
User: abhik35
train-test-split,Coursera Speccialization Courses
User: adicherlavenkatasai
train-test-split,Customer Retention Deep Learning Model
User: adil-imran
train-test-split,Classification model to categorize clothing items into distinct classes
User: aditijoshi613
train-test-split,
User: alaa-aleryani
train-test-split,Model selection crucial in loan approval prediction project. Random Forest outperformed Logistic Regression, emphasizing importance of choosing appropriate models for accurate predictions.
User: aloray
train-test-split,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.
User: ava33343
train-test-split,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.
Organization: best-brain-gang
train-test-split,📁 Repo for python_splitter Python package. This package can split Images into Train, Test, Validation folders automatically by shuffling media/images for machine learning.
User: bharatadk
Home Page: https://pypi.org/project/python-splitter/
train-test-split,A simple example of random state in train test split using python
User: bhattbhavesh91
train-test-split,This is a project where I use the Random Forest Regression and XGBoost Machine Learning Techniques to held predict the Sales Price of Houses..
User: bradyfisher
train-test-split,This 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.
User: bradyfisher
train-test-split,To model the demand for shared bikes with the available independent variables
User: chinmayeeguru
train-test-split,Understanding Train-Test-Split in R
User: eben2020-hp
train-test-split,It is a Turkish BERT-based model that will analyze people's bank complaints and classify them according to one of eight categories.
User: elifftosunn
train-test-split,To design a predictive model to determine the potential customers who will purchase if you send the advertisement
User: enamahirah
train-test-split,GraphPart, a data partitioning method for ML on biological sequences
Organization: graph-part
Home Page: https://pypi.org/project/graph-part/
train-test-split,Machine Learning with Scikit Learn
User: iamkirankumaryadav
train-test-split,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.
User: jaanvig
train-test-split,Predicting The Energy Output Of Wind Turbine Based On Weather Condition DEMO LINK : https://youtu.be/ICfu49Ud2HU
User: jagadeeshpj
train-test-split,Scientific programming through the SKLearn / Scikitlearn library
User: jesussantana
train-test-split,Repository of all exercises and assignments in 365 Data Science Machine Learning Course
User: jigarpatel108
train-test-split,The purpose of this project is to develop a machine learning model that predicts employee attrition (whether an employee will leave the company) and department assignment (which department an employee belongs to) based on various factors. These factors include age, travel frequency, education level, job satisfaction, marital status, and more.
User: jmarihawkins
train-test-split,To create a classification model to predict the gender (male or female) based on different parameters using given csv file.
User: lakshmikeerthi-22
train-test-split,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.
User: mahtabek
train-test-split,`Spltr` is a simple PyTorch-based data loader and splitter. It may be used to load arrays and matrices or Pandas DataFrames and CSV files containing numerical data with subsequent split it into train, test (validation) subsets in the form of PyTorch DataLoader objects.
User: maksymsur
train-test-split,
User: manojkumar-449
train-test-split,Prevendo o Nível de Satisfação dos Clientes do Santander.
User: marinafajardo
train-test-split,A time slicer for training and testing temporally correlated Machine Learning models.
User: marmurar
train-test-split,You can separate the images in your file as a train test txt file in the yolo format.
User: mehmetokuyar
train-test-split,1. train_test_split 2.K_fold 3.LeaveoneOut 4.Cross Validation Score 5.Logistic Regression
User: moindalvs
train-test-split,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.
User: neonostrich
train-test-split,This library allows reading and converting bounding box annotations in many popular formats
User: odancona
Home Page: https://bboxconverter.readthedocs.io/en/latest/
train-test-split,Sample programs with basic machine learning concepts
User: pramodiperera
train-test-split,Learning Project ML - Diabetes Prediction
User: quantummonkey
train-test-split,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.
User: rishabh1882
train-test-split,This repository contains introductory notebook for logistic regression
User: sanketmaneds
train-test-split,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.
User: shayleaschreurs
train-test-split,
User: shohaha
train-test-split,This ML⚒ project is to prove the dependencies of a motor🛠 in an everyday pump system👷♂️👨🏭
User: subhayuroy
train-test-split,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.
User: thakursiddhesh
train-test-split,GroupSplit is a module to help split datasets into train and test sets for data science and machine learning projects.
User: v0xp0p
train-test-split,Model-Validation-Methods
User: vaitybharati
train-test-split,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
User: vaitybharati
train-test-split,This is an algorithm for evenly partitioning.
User: yu9824
Home Page: https://pypi.org/project/kennard-stone/
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.