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Faculty Informatic Institute for Systemarchitektur, Professor for DatenbankenDiplomarbeitFEATUREBASIERTE CLASSIFICATION ON ZEITREIHENDATENSTZEN MIT MASCHINELLEM LERNER Julius Senior Mate. NR.: 3855516Betreut
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01
Identify the features or attributes of the data that will be used for classification.
02
Select a classification algorithm that is suitable for feature-based classification.
03
Divide the data into training and testing sets.
04
Train the classification model using the training set.
05
Evaluate the model's performance using the testing set.
06
Make predictions on new data based on the trained model.

Who needs feature-basierte klassifikation von?

01
Data scientists and machine learning engineers who are working on classification tasks.
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Researchers who are working with large datasets and need to categorize and organize the data based on its features.
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Companies and organizations that want to automate decision-making processes based on specific features of their data.
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Feature-basierte Klassifikation von is a classification based on features or characteristics.
Companies or individuals who have products or services that need to be classified based on specific features.
Feature-basierte Klassifikation von can be filled out by providing detailed information about the features of the product or service and selecting the appropriate classification category.
The purpose of feature-basierte Klassifikation von is to organize and categorize products or services based on their distinct features for easier identification and comparison.
Information such as product features, classification category, and any relevant details that help in accurately classifying the product or service.
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