Showing 13 open source projects for "weka arff"

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  • 1
    JAETL - Just Another ETL Tool

    JAETL - Just Another ETL Tool

    Just Another ETL Tool

    JAETL - Just Another ETL tool is a tiny and fast ETL tool to develop data warehouse. JAETL allows to Extract data from ARFF (Weka), CSV, and SQL, Transform the data with join, replace missing values, remove duplicates, mapping filtering, variable selection, and Load the data into SQL server and export to CSV and ARFF.
    Downloads: 0 This Week
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  • 2
    Twitter Research Data Collector
    It gives facility of collecting tweets through Twitter Streaming API w.r.t different search criteria and to save tweets in CSV and ARFF (WEKA) file formats.
    Downloads: 0 This Week
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  • 3

    ml2db

    Multi-label machine learning to database

    A Java harness to load data from database, create Weka ARFF and Mulan ARFF+XML files, run machine learning experiments and save the evaluation and predictions to database. If using this code, please quote: BMC Bioinformatics, EnzML: multi-label prediction of enzyme classes using InterPro signatures, Luna De Ferrari, Stuart Aitken, Jano van Hemert and Igor Goryanin http://www.biomedcentral.com/1471-2105/13/61
    Downloads: 0 This Week
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  • 4

    Cost-sensitive Classifiers

    Adaboost extensions for cost-sentive classification

    ...They are the meta algorithms which requires base algorithms e.g. Decision Tree Moreover, Voting criteria is also required e.g. Minimum expected cost criteria Input also requires to load an arff file and a cost matrix (sample arff and cost files are uploaded for users' reference) This extension uses weka for classification and generates the classification model along with confusion matrix. For given dataset and cost matrix
    Downloads: 0 This Week
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  • 5
    WAP RSSI 2 ARFF

    WAP RSSI 2 ARFF

    This program scans WAP RSSI readings and turns then into an ARFF file.

    ...It scan for wireless access points (WAPs) and notes their Base Station ID or BSSID and their Received Signal Strength Indicator or RSSI. This data, along with an identifier for the physical location or 'ROOM', and the name of the computer it is being run on are stored as an ARFF file, which is compatible with programs such as WEKA and RAPIDMINER.
    Downloads: 0 This Week
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  • 6
    weka utility is a simple tool to read weka log and merge arff file and more....
    Downloads: 0 This Week
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  • 7
    stocleka is a project divided into a UI and a library for cleaning user stories and converting them to arff files (used for Weka). it may be mainly used for research and scientific purposes.
    Downloads: 0 This Week
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  • 8
    Data Mining LiWeCool
    DM LiWeCool is a tool for preprocessing light-weight CSV data files as Weka-compatible. It includes merging different header lines into one, editing values (encoding, categorizing, etc) and saving data as ARFF or XRFF (Weka native). It is Java-based.
    Downloads: 0 This Week
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  • 9
    Excel to Arff converter. You can easily convert the excel datas will be used data mining process to arff file format and then easily analyze your datas and results using WEKA Data Mining Utility.
    Downloads: 2 This Week
    Last Update:
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  • 10
    Dataset Retrieval through Intelligent Agents (DARIA): is an Open Source project for facilitating the construction of ARFF data set files for use with WEKA or any such Machine Learning/Data Mining Software through the use of Intelligent Agents.
    Downloads: 0 This Week
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  • 11
    This tool acts as a preprocessor and transforms data from a database into arff format for weka data mining. Vertical to horizontal transformation for association analysis. The tool can use databases for which an OleDB adapter exists. Vb.Net for Win32
    Downloads: 0 This Week
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  • 12
    A utility to extract data from RDBMSs and convert into .arff file format required by WEKA data mining tool set, both interactive wizard and batch working modes.
    Downloads: 0 This Week
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  • 13
    ktdata is a C++ library for accessing tabular data, like from CSV files. Its goals are: 1. object design 2. portability (Linux and Windows support at least) 3. high performance 4. support for common data file formats, like CSV, ARFF (Weka), etc.
    Downloads: 0 This Week
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