Topic: decision-tree-classification Goto Github
Some thing interesting about decision-tree-classification
Some thing interesting about decision-tree-classification
decision-tree-classification,Decision Tree and Artificial Neural Network for Cell of Cancer
User: afifadayu
decision-tree-classification,
User: akanksha-15-priya
decision-tree-classification,Sentiment Analysis of Movies Dataset
User: amiegirl
decision-tree-classification,Implementation of Decision Tree algorithm in python, this is a basic implementation and will be helpful for beginners to start, understand and implement Decision Trees. This repository will help in understanding decision trees using Python. This also includes plotting ROC curve, confusion metrics etc.
User: amit-raj-repo
decision-tree-classification,ML model that creates a decision tree to classify recipes into cuisines based on their ingredients.
User: ananya-k15
decision-tree-classification,Build and evaluate classification model using PySpark 3.0.1 library.
User: ansu-john
decision-tree-classification,In this project the data is been used from UCI Machinery Repository. Main aim of this project is to predict telling tumor of each patient is Benign (class β 2) or Malignant (class β 4) the models used are β Decision tree Classification, Logistic Regression, K-Nearest Neighbors, SVM, Kernel SVM, NaΓ―ve-Bayes and Random Forest Classification.
User: bhavya840
decision-tree-classification,Full machine learning practical with Python.
User: dshah98
decision-tree-classification,Full machine learning practical with R.
User: dshah98
decision-tree-classification,House Prices Prediction and Credit Default Risk Prediction competitions. Advanced decision tree-based regression and classification models are used.
User: georgemuriithi
decision-tree-classification,Decision Tree is a decision-making tool that uses a flowchart-like tree structure or is a model of decisions and all of their possible results, including outcomes, input costs and utility. Decision-tree algorithm falls under the category of supervised learning algorithms. It works for both continuous as well as categorical output variables. Decision tree classification observes features of an object and trains a model in the structure of a tree to predict the class of the data.
User: girirajv10
decision-tree-classification,MACHINE LEARNING ALGORITHMS
User: hanifaelahi
decision-tree-classification,Implementation of Decision Tree classification algorithm in Python using Pandas, NumPy and Scikit-Learn.
User: ivalada
decision-tree-classification,All my Machine Learning Projects from A to Z in (Python & R)
User: joycechidi
decision-tree-classification,Prediction of students' dropout using classification models. Data visualisation, feature selection, dimensionality reduction, model selection and interpretation, parameters tuning.
User: lezippo
decision-tree-classification,I've demonstrated the working of the decision tree-based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample. All the steps have been explained in detail with graphics for better understanding.
User: milaan9
decision-tree-classification,Some of my Python Projects
User: musaddiq625
decision-tree-classification,If you miss payments or you don't pay the right amount, your creditor may send you a default notice, also known as a notice of default. If the default is applied it'll be recorded in your credit file and can affect your credit rating. An account defaults when you break the terms of the credit agreement.
User: nitingour1203
decision-tree-classification,Breast Cancer Prediction with Logistic Regression Classification gives an accuracy of 96.70%. apart from this Decision Tree Classification gives more accuracy along with LRC. Dataset can be available on UCI Machine Learning.
User: shlok1810
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