Decision Tree Dataset Csv, This project implements a decision tree

Decision Tree Dataset Csv, This project implements a decision tree algorithm to analyze student performance data. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. In the example, a person will try to decide if he/she should go to a comedy show or not. The project includes full data preprocessing, model training, performance evaluation (accuracy, precision, recall, F1-score), and visual decision tree interpretation for transparent risk analysis. 97-101, 1992], a classification method which uses linear programming to construct a decision tree. WHO has recommended maximum permissible limit of pH from 6. isna (). This dataset provides a multi-modal collection of features derived from single-unit electrophysiology recordings, aiming to characterize neuronal units based on their morphological, temporal, and spectral properties, as well as their representation in a latent embedding space and their classification via a neuro-symbolic model. Let’s build a regression tree using Scikit-Learn’s DecisionTreeRegressor class, training it on a noisy quadratic dataset with max_depth=2: Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. metrics import accuracy_score, classification_report st. read_csv ("student_performance. head ()) print (features_df. 1 in such a way that the new entry becomes the part of the given dataset. title ("🎓 Student Performance Prediction App") st. tree import DecisionTreeClassifier from sklearn. The topmost node in a decision tree is known as the root node. 1. . Jan 27, 2026 · A Decision Tree, conversely, is a white-box model. 3 days ago · Artificial Intelligence (SE314T) Question: 02 Use the given dataset and inspect the structure features_path = "Feature_dataset. Practice and apply your data skills with curated datasets in DataLab Decision Tree is a type of supervised learning algorithm that is mostly used for classification problems. A decision tree is a flowchart-like tree structure where an internal node represents feature (or attribute), the branch represents a decision rule, and each leaf node represents the outcome. A Decision Tree is a Flow Chart, and can help you make decisions based on previous experience. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. A good Dataset for Begineers to start their ML journey makes data Cleaning {EDA} and visualizing easier. It is also the indicator of acidic or alkaline condition of water status. csv") st. What is Classification? Classification is the process of dividing the datasets into different categories Decision Trees are also capable of performing regression tasks. CSV files, the correct resulting decision tree in various graphics formats (such as JPG and SVG) and step-by-step instructions on how Explore this free Decision Tree Classification dataset. csv" features_df = pd. Flexible Data Ingestion. R to explore various factors About Dataset A Dataset with varying salaries of Employes and their Position according to their Years of experience. Jan 28, 2026 · 7- Decision Tree learner Node output to input Decision Tree Node input 8- Decision Tree output to input ROC Node. It includes data preprocessing, feature engineering, model building (Linear Regression, Decision Tree, Random Forest), and validation techniques (cross-validation, grid search). It utilizes datasets such as student-mat. Relevant features were selected using an exhaustive search in the space of 1-4 features and 1-3 separating planes. This repository aims at familiarizing with training and testing Decision Tree and Random Forest classification model comprising of 5 parts: loading & analyzing dataset; checking if imbalanced dataset; finding best Decision Tree and Random Forest; showing most important features; visualizing tree. These datasets include the raw data as . A decision tree is a graphical representation of all the possible solutions to a decision based on certain conditions. 5. AI-powered drug recommendation system using machine learning models (SVM, Random Forest, Decision Tree) to predict drug ratings and provide personalized recommendations based on patient conditions Jul 23, 2025 · Using SVM to perform classification on a non-linear dataset Decision Tree Decision Tree Implementing Decision tree Decision Tree Regression using sklearn Random Forest Random Forest Regression in Python Random Forest Classifier using Scikit-learn Hyperparameters of Random Forest Classifier Voting Classifier using Sklearn Bagging classifier We’re on a journey to advance and democratize artificial intelligence through open source and open science. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Decision Tree In this chapter we will show you how to make a "Decision Tree". 5 to 8. pH value: PH is an important parameter in evaluating the acid–base balance of water. csv file contains water quality metrics for 3276 different water bodies. subheader ("📊 Dataset Preview") Content The water_potability. write ("Data Mining & Machine Learning using Decision Tree") # Load Dataset df = pd. Practice DATASET for Decision Trees learning Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. The project includes full data preprocessing, model training, performance evalu This repository contains a comprehensive analysis of the California Housing dataset to predict median house values. read_csv (features_path) print ("\nRAW FEATURE DATA INFO") print (features_df. Oct 31, 1995 · Proceedings of the 4th Midwest Artificial Intelligence and Cognitive Science Society, pp. csv, student-por. It breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. sum ()) print Jul 14, 2025 · SHAP also supports interpretation of other models like decision trees, random forests, or even neural networks. Example with Decision Tree Classifier on Iris Dataset Loads the Iris dataset with features of different flower species. Code: i mport pandas as pd from sklearn. tree import DecisionTreeClassifier, plot_tree from sklearn. This repository is a collection of 6 original synthetic datasets (called the Cooking, Gym, Diet, License, StressLevel, and Conditions dataset) intended to teach how to calculate decision trees in Artificial Intelligence. Good for regression Techniques like Decision Tree, Simple Linear Regression, Multiple Regression and CatBoost or XGBoost Built a Decision Tree machine learning model to predict credit risk and loan default using real-world financial data. Trains a DecisionTreeClassifier on the training data. Welcome to the Decision Trees in Machine Learning repository! This project offers resources for understanding and implementing decision trees, a fundamental algorithm for classification and regress Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. 3 days ago · Implement Decision Tree using table. Explore and run machine learning code with Kaggle Notebooks | Using data from Car Evaluation Data Set It is a sample of binary classifier, and you can use the training part of the dataset to build a decision tree, and then use it to predict the class of a unknown patient, or to prescribe it to a new patient. csv, and student-merge. info ()) print ("\nMissing values per column:\n", features_df. This project uses a Decision Tree Classifier to predict whether a customer will subscribe to a bank term deposit based on their personal and marketing-related information. It learns to partition on the basis of the attribute value. Selected dataset is data employee recruitment. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Splits the data into training and test sets. This works for both categorical and continous dependent variables. (here you can evaluate your model base on AUC value) Inspiration Use machine learning to determine which physiochemical properties make a wine 'good'! Acknowledgements Built a Decision Tree machine learning model to predict credit risk and loan default using real-world financial data. Jun 13, 2025 · About Dataset About : The Play Tennis Dataset 🎾 is a simple yet powerful dataset frequently used in machine learning tutorials to demonstrate classification algorithms , especially decision trees and rule-based models. mj881, u16ew, oixz, ljt4to, rk1s, oy9w, rqrny, e8sd, xvrbpg, 9kwd,