usman-saghla /
decision-tree-classification-Social_Ads
This repository contains a hands-on Jupyter Notebook that demonstrates how to build, evaluate, and visualize a Decision Tree classifier using the Social_Network_Ads dataset.
34/100 healthLoading repository data…
sukruta230901 / repository
This repository contains the Lab practices of Machine Learning performed in Jupyter Notebook using python language. This repo consists of Decision Tree Classifier model to classify the given data.
A transparent discovery signal based on current public GitHub metadata.
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
This repo contains Lab practices of Machine Learning performed in Jupyter Notebook using Python language
🚀 LAB-4: Decision Tree Classifier
◾ LAB 4 ipynb file consists of the basic python coding required to perform the Decision Tree Classifier on a given data set and classify the data accurately. This code files uses the bill_authentication.csv dataset file to perform the Decision Tree Classifiecation and Visualizes the classification tree using matplotlib and seaborn libraries.
Selected from shared topics, language and repository description—not editorial ratings.
usman-saghla /
This repository contains a hands-on Jupyter Notebook that demonstrates how to build, evaluate, and visualize a Decision Tree classifier using the Social_Network_Ads dataset.
34/100 healthRajshekokar3 /
This repository contains a Jupyter Notebook for building and analyzing a Decision Tree Classifier. The notebook demonstrates the step-by-step process of importing data, preprocessing, model training, and evaluation
27/100 healthalinapradhan /
This repository contains a Jupyter Notebook implementation of a Decision Tree Classifier using PySpark. The project demonstrates how to preprocess data, train a decision tree model, evaluate its performance, and visualize results in a scalable environment.
Amina-bzr /
This repository contains solutions to a set of machine learning exercises, focusing on decision tree classifiers, cross-validation methods, and agglomerative clustering. The provided Jupyter notebook includes implementations and analyses for the exercises outlined in the readme.md file.
27/100 healthkasif-zisan /
This repository contains my Jupyter Notebook where I predicted Darknet traffic using the CIC-Darknet2020 dataset. I used Decision Tree Classifier and Logistic Regression for the traffic prediction. I also showed difference between the performance of the two models.
27/100 healthhiraa-ahmad /
This repository contains code for a data science internship project on building a decision tree classifier for the diabetes dataset. It aims to predict diabetes occurrence based on various factors. Explore the provided Jupyter notebooks for data analysis, model training, and evaluation. Feel free to clone the repo, experiment, and contribute
27/100 health