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CSV to ARFF Converter [2025]
Transform CSV data into WEKA ARFF format with intelligent attribute type detection and customization options.
Upload CSV
Drag and drop your CSV file here or click to browse
Key Features
- Intelligent attribute type detection for numeric, nominal, string, and date data.
- Flexible header options with support for first or second row as column names.
- Automatic class attribute detection for machine learning tasks.
- Custom attribute type configuration per column.
- Option to skip irrelevant columns during conversion.
- Support for missing value handling.
- WEKA-compatible ARFF output with proper escaping and formatting.
- Preview of detected attributes and their types before conversion.
Common Use Cases
Machine Learning
- • WEKA data preparation
- • Classification tasks
- • Regression analysis
- • Feature selection
Data Analysis
- • Dataset preprocessing
- • Attribute selection
- • Data cleaning
- • Type conversion
Research
- • Academic studies
- • Data visualization
- • Statistical analysis
- • Model training
About ARFF Format
The Attribute-Relation File Format (ARFF) is a standard format used by WEKA machine learning software. It provides a way to describe datasets with different attribute types and is widely used in the data mining and machine learning community.
ARFF Structure:
@RELATION dataset_name @ATTRIBUTE attribute1 NUMERIC @ATTRIBUTE attribute2 {value1, value2, value3} @ATTRIBUTE attribute3 STRING @ATTRIBUTE class {class1, class2} @DATA 1.0,value1,"some text",class1 2.0,value2,"more text",class2
Frequently Asked Questions
How do I prepare my CSV file?
Your CSV file should have a header row with column names. The tool supports both standard CSV formats and options to use the second row for column names. For machine learning tasks, typically the last column contains the class label.
What attribute types are supported?
The converter supports all standard ARFF attribute types: NUMERIC for numbers, NOMINAL for categorical data (automatically detected for limited unique values), STRING for text data, and DATE for date/time values. You can also choose to skip columns during conversion.
How are missing values handled?
Missing values in the CSV are converted to ARFF's standard missing value indicator '?'. You can configure whether empty cells should be treated as missing values or maintained as empty strings.
Is the output compatible with WEKA?
Yes, the generated ARFF files are fully compatible with WEKA and other tools that use the ARFF format. The converter follows the ARFF specification and properly handles special characters, quotation, and escaping.
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