WEKA Assignment Help By Statistics Experts

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 WEKA Assignment Help
 

What is WEKA?

Weka is a prime software package that is used for data mining tasks. It is a collection of machine learning algorithms.

It contains numerous tools for data pre-processing, regression and correlation, data clustering, and data visualization. It can also be used for developing new machine learning schemes.

WEKA algorithm can be applied directly to a data set of the Java code. It is a user-friendly application.

It is intended for those who are familiar with data mining techniques and database analysis.

By using this software, users can view and analyze ARFF (Attribute-Relation File Format) data files. The analysis result can be stored either in ARFF or users can protect it as a JDBC database.

Features of Weka

  • Open Source: Weka is available as open source software which operates under the GNU platform.
  • GUI (Graphical User Interface): It has a Graphical User Interface. It allows you to complete your machine learning projects without programming.
  • CLI (Command Line Interface): It allows all features of this software to be used from Command Line Interface. CLI can be handy for scripting large jobs.
  • Java API: Java API is written in Java. It provides an Application Programming Interface. Java API is well properly documented and also promotes integration into your applications.
  • Documentation: Weka is suitable for there exist manuals, books, and MOOC courses. It impacts users with skills to use it effectively.

Subtopics of WEKA Assignment Help

Our weka assignment help experts also covered Subtopics of weka assignment that given below.

            

JRip Assignment Help

ZeroR Assignment Help

NaiveBayes Assignment Help

Ridor Assignment Help

DBSCAN Assignment Help

Apriori Assignment Help

            

JRip Assignment Help

JRip stands for Joint Reserve Intelligence Program. It implements a propositional rule learner.

ZeroR Assignment Help

It is the simplest organization method which depends on the target and ignores all predictors.

NaiveBayes Assignment Help

It is a classification technique based on Bayes' Theorem. It is an assumption of independence among predictors.

Ridor Assignment Help

It generates a default rule first and then the exceptions for the default rule.

DBSCAN Assignment Help

It stands for Density-based spatial clustering of applications with noise.

Apriori Assignment Help

It is an algorithm for frequent itemset mining and association rule learning over transactional databases.

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