Jhansi Rani Kunaparaju

  F.)Load each dataset and observe the following: 1. List the attribute names and they type. 2. Number of records in each dataset 3. Identify the class attribute (if any) 4. Plot Histogram 5. Determine the number of records for each class. 6. Visualize the data in various dimensions Procedure : 1) Open the WEKA tool and Select the Explorer option. 2) A new window will be opened which consists of six tabs – Preprocess, Classify,  Cluster, Associate, Select Attributes and Visualize. 3) In the Preprocess tab, Click the “Open file” option. 4) Go to C:\Program Files\Weka-3-8-6\data for finding different existing .arff datasets. 5) Click on any of the dataset for loading the data and then the data will be displayed as shown. 6) Here Weather.arff dataset is chosen as sample for all the observations. 1 . List the attribute names and their type . There are 5 attributes and its data type presented in the loaded dataset Weather.arff. S.NO. ATTRIBUTE NAME DATA TYPE 1     ...

 Study the arff file format Explore the available data sets in WEKA. Load a  data set (ex. Weather dataset, Iris dataset, etc.) ANS: 1. An ARFF (Attribute-Relation File Format) file is an ASCII text file that  describes a list of instances sharing a set of attributes. 2. ARFF files have two distinct sections – The Header & the Data. • The Header describes the name of the relation, a list of the attributes,  and their types. • The Data section contains a comma separated list of data Example of student data set creation: ///////////////\\\\\\\\\\\\\\\\\copy from ur notes Available Datasets in WEKA: There are 25 different datasets are available in WEKA (C:\Program Files\Weka-3- 8-6\data) by default for testing purpose. All the datasets are available in .arff format. Those datasets are listed below. ///////////Open program files and  open weka--data--- and write all the dataset names///////////////

 //2b// Downloading and/or installation of WEKA data mining toolkit. Go to the Weka website, http://www.cs.waikato.ac.nz/ml/weka/ , and download the software. Select the appropriate link corresponding to the version of the software based on your operating system and whether or not you already have Java VM running on your machine. The link will forward you to a site where you can download the software from a mirror site. Save the self-extracting executable to disk and then double click on it to install Weka. Answer yes or next to the questions during the installation. Click yes to accept the Java agreement if necessary. After you install the program Weka should appear on your start menu under Programs (if you are using Windows). Running Weka from the start menu select Programs, then Weka. You will see the Weka GUI Chooser. Select Explorer. The Weka Explorer will then launch. //2c// Understand the features of WEKA toolkit such as Explorer, Knowledge Flow interface, Experimenter, comm...

  Explore machine learning tool“WEKA”//2.a// Explore WEKA Data Mining/Machine Learning Toolkit. ANS: WEKA(Waikato Environment for Knowledge Analysis) an open-source software provides tools for data preprocessing, implementation of several Machine Learning algorithms, and visualization tools so that we can develop machine learning techniques and apply them to real-world data mining problems. Features of WEKA - Preprocessor – Most of the Data is Raw. Hence, Preprocessor is used to clean the noisy data. Classify – After preprocessing the data, we assign classes or categories to items. Cluster – In Clustering, a dataset is arranged in different groups/clusters based on some similarities. Associate – Association rules highlight all the associations and correlations between items of a dataset. Select Attributes – Every dataset contains a lot of attributes; only significantly valuable attributes are selected for building a good model. Visualize – In Visualization, different plot matrices ...