Getting started with weka Loading Instances Text Classification How to use R in Weka How to use CPython Scripting in Weka?Simple Comparison of Weka Interfaces Getting Started With Jython in Weka Mistakes easily made when using KnowledgeFlow

Simple Comparison of Weka Interfaces

Remarks:

Explorer

pro:

do all things quickly
give a quick and comprehensive view of data structure

cos: can't save the process;

Experimenter

pro:

compare several models at once, e.g., run 3 different classifiers against 5 datasets all together, and see the compared result at one place;
experiment can be saved

KnowledgeFlow

pro:

do almost all things that Explorer can do
can save the process

cos:

KF can't do Experimenter's job, as it doesn't support loops, but ADAMS can help;
KF can't access low-level functionalities inside Weka API;

simpleCLI

pro: run similar tasks of what Explorer does using command line

cos: it can't access all functionalities of Weka API, Jython or Groovy scripting is recommended for this task.

Workbench

pro: it gathers all other interfaces together into one place

simpleCLI and Jython examples

simpleCLI

go to simpleCLI, enter the following code

java weka.classifiers.rules.ZeroR -t path/to/a-file-of-dataset

Jython Example

codes from Advanced Weka MOOC course lesson 5.1

# imports
import weka.core.converters.ConverterUtils.DataSource as DS
import weka.filters.Filter as Filter
import weka.filters.unsupervised.attribute.Remove as Remove
import os

# load data
data = DS.read(os.environ.get("MOOC_DATA") + os.sep + "iris.arff")

# remove class attribute
rem = Remove()
rem.setOptions(["-R", "last"])
rem.setInputFormat(data)
dataNew = Filter.useFilter(data, rem)

# output filtered dataset
print(dataNew)

Contributors

Topic Id: 8042

Example Ids: 25974

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