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In supervised learning, what is the role of the training dataset?
In supervised learning, what is the role of the training dataset?
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In supervised learning, what is the role of the training dataset?
To evaluate the model's performance
To tune hyperparameters
To train the model to learn patterns
To visualize data
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The training dataset is used to train the model, allowing it to learn patterns and relationships in the data.
Questions & Step-by-step Solutions
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Q
Q: In supervised learning, what is the role of the training dataset?
Solution:
The training dataset is used to train the model, allowing it to learn patterns and relationships in the data.
Steps: 5
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Step 1: Understand that supervised learning is a type of machine learning where we teach a model using labeled data.
Step 2: Know that a training dataset is a collection of examples that includes both input data and the correct output (labels).
Step 3: The model uses the training dataset to learn by finding patterns and relationships between the input data and the output labels.
Step 4: As the model processes the training dataset, it adjusts its internal parameters to improve its predictions.
Step 5: After training, the model can then be tested on new, unseen data to see how well it learned from the training dataset.
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