36 lines
1.1 KiB
CSV
36 lines
1.1 KiB
CSV
# Sample dataset for AutoML pipeline builder plugin
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# This dataset is a simplified example and may not be suitable for all AutoML tasks.
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# Replace this with your actual dataset for optimal results.
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#
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# Columns:
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# feature1: Numerical feature (e.g., age, income)
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# feature2: Categorical feature (e.g., city, product type) - encoded as strings
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# target: Target variable (e.g., churn, conversion) - binary (0 or 1)
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feature1,feature2,target
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25,New York,0
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30,Los Angeles,1
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40,Chicago,0
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22,Houston,0
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35,Phoenix,1
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48,Philadelphia,1
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28,San Antonio,0
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32,San Diego,1
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45,Dallas,0
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27,San Jose,0
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31,Austin,1
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38,Jacksonville,0
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24,Fort Worth,0
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41,Columbus,1
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29,Charlotte,0
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33,San Francisco,1
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46,Indianapolis,1
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23,Seattle,0
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36,Denver,1
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49,Washington,1
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# Add more data rows here. Aim for a larger dataset (hundreds or thousands of rows) for better AutoML performance.
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# Example:
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# 52,Miami,0
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# 39,Boston,1
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# Consider adding missing values (e.g., empty strings) to test the pipeline's handling of missing data.
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# For categorical features with many unique values, consider using techniques like one-hot encoding or target encoding. |