KNIME Software

Prepared by:Amr Mohammad Mounir El-bora’ay Essa

Ahmad Yasser Ibrahim El EnanyAhmad Mohammad Jamal El-Din

Mohammad Atef Mahmoud

Data Mining

VS

Contents

IntroductionFeaturesFunctions & toolsFlat file appearance

Introduction• KNIME:

Stands for (KoNstanz Information MinEr).It is a user friendly, coherent open source data analytics, reporting and integration platform.KNIME is developed by Prof. Michael Berthold's group at the University of Konstanz in Germany.

It uses CSV format ( Comma Separated Values).It is written in java programming language.It is open source software.It started January 2004.

Features

Modular Data Pipeline EnvironmentLarge collection of Data Mining techniquesData and Model VisualizationsInteractive Views on Data and ModelsJava Code Base as Open Source ProjectIntegration with: R Library, Weka, etc.Based on the Eclipse Plug-in technology

Functions & toolsClassification.Association rules.Clustering .Neural networks.Naïve Bayes.K nearest neighbour.Decision trees.

Flat file in .CSV format(Heart-Disease):Age, gender, chest_pain_type, cholesterol, exercise_induced_angina,class63,male,typ_angina,233,no,not_present67,male,asympt,286,yes,present67,male,asympt,229,yes,present38,female,non_anginal,?,no,not_present

WEKAIt stands for (Waikato Environment for Knowledge Analysis).It is a set of software for machine learning and data mining.It was developed at the University of Waikato, New Zealand.It uses ARFF format ( Attribute Relation File Format).

It is written in java programming language.It is open source software.It started 1993.

features

49 data preprocessing tools76 classification/regression algorithms8 clustering algorithms10 feature selection algorithms3 algorithms for finding association rules

3 graphical user interfaces–“The Explorer” (exploratory data analysis)–“The Experimenter” (experimental environment)–“The Knowledge Flow” (new process model inspired interface).

Functions and toolsClassification.Association rules.Clustering .Neural networks.Naïve Bayes.K nearest neighbour.Decision trees.

Flat file in .ARFF format(Heart-Disease):@relation heart-disease@attribute age numeric@attribute gender { female, male}@attribute chest_pain_type{ typ_angina, asympt, non_anginal, atyp_angina}@attribute cholesterol numeric@attribute exercise_induced_angina{ no, yes}@attribute class { present, not_present}

@data63,male,typ_angina,233,no,not_present67,male,asympt,286,yes,present67,male,asympt,229,yes,present38,female,non_anginal,?,no,not_present

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