Text classification model
Text classification is a machine learning technique used to assign predefined categories or labels to text data. It involves training a model on a labeled dataset, where each text sample is associated with a specific category, allowing the model to recognize patterns and features in the text that correspond to different categories. This technique is particularly useful for applications such as spam detection, sentiment analysis, and topic categorization, benefiting businesses and researchers who need to organize and analyze large volumes of text data efficiently.
Text classification model was discovered on November 22nd 2021 and it currently has a search volume of 390 with a growth of +456%.
Growth
- Exploding
- Regular
- Peaked
Speed
- Exponential
- Constant
- Stationary
Seasonality
- High
- Medium
- Low
Volatility
- High
- Average
- Low
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