Media Summary: Evaluating classifiers on iris data set and visualizing misclassifications. License: GNU GPL + CC Music by: ... Making predictions with classification tree and logistic regression. The data is no longer available. Follow the procedure with any ... Explanation of distance measurement between data points and a simple use of hierarchical clustering in the

Getting Started With Orange 07 - Detailed Analysis & Overview

Evaluating classifiers on iris data set and visualizing misclassifications. License: GNU GPL + CC Music by: ... Making predictions with classification tree and logistic regression. The data is no longer available. Follow the procedure with any ... Explanation of distance measurement between data points and a simple use of hierarchical clustering in the Dimensionality reduction with principal component analysis. License: GNU GPL + CC Music by: How to transform text into numerical representation (vectors) and how to find interesting groups of documents using hierarchical ... Interactive explanation of k-means algorithm and how the algorithm can potentially fail. For more information on teaching or ...

Photo Gallery

Getting Started with Orange 07: Model Evaluation and Scoring
Getting Started with Orange 01: Welcome to Orange
Getting Started with Orange 08: Add-ons
Getting Started with Orange 16: Text Preprocessing
Getting Started with Orange 06: Making Predictions
Data Mining Lab 7  Association Analysis in Orange
Getting Started With Orange 05: Hierarchical Clustering
Getting Started with Orange 04: Loading Your Data
Getting Started with Orange 09: Principal Component Analysis
Introduction to Analysis using Orange
Getting Started with Orange 17: Text Clustering
Getting Started with Orange (3): Workflow and Linking Widgets
View Detailed Profile
Getting Started with Orange 07: Model Evaluation and Scoring

Getting Started with Orange 07: Model Evaluation and Scoring

Evaluating classifiers on iris data set and visualizing misclassifications. License: GNU GPL + CC Music by: ...

Getting Started with Orange 01: Welcome to Orange

Getting Started with Orange 01: Welcome to Orange

Introduction to

Getting Started with Orange 08: Add-ons

Getting Started with Orange 08: Add-ons

Installing add-ons in

Getting Started with Orange 16: Text Preprocessing

Getting Started with Orange 16: Text Preprocessing

How to work with text in

Getting Started with Orange 06: Making Predictions

Getting Started with Orange 06: Making Predictions

Making predictions with classification tree and logistic regression. The data is no longer available. Follow the procedure with any ...

Data Mining Lab 7  Association Analysis in Orange

Data Mining Lab 7 Association Analysis in Orange

Performing association analysis in

Getting Started With Orange 05: Hierarchical Clustering

Getting Started With Orange 05: Hierarchical Clustering

Explanation of distance measurement between data points and a simple use of hierarchical clustering in the

Getting Started with Orange 04: Loading Your Data

Getting Started with Orange 04: Loading Your Data

Loading your data in

Getting Started with Orange 09: Principal Component Analysis

Getting Started with Orange 09: Principal Component Analysis

Dimensionality reduction with principal component analysis. License: GNU GPL + CC Music by: http://www.bensound.com/ ...

Introduction to Analysis using Orange

Introduction to Analysis using Orange

Getting started

Getting Started with Orange 17: Text Clustering

Getting Started with Orange 17: Text Clustering

How to transform text into numerical representation (vectors) and how to find interesting groups of documents using hierarchical ...

Getting Started with Orange (3): Workflow and Linking Widgets

Getting Started with Orange (3): Workflow and Linking Widgets

Welcome to the third lesson of '

Getting Started with Orange 12: k-Means Explained

Getting Started with Orange 12: k-Means Explained

Interactive explanation of k-means algorithm and how the algorithm can potentially fail. For more information on teaching or ...