Train and Test Error dependence on size of data
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I was reading about Adaboost Alogorithm and learned that if initially we split the dataset equally for training and testing, apply the algorithm. And then gradually start increasing the size of train dataset (and lower the test set) for each iteration of the algorithm , the difference between the training error and test error starts decreasing.
I wanted to understand the reason behind this and also the impact of the size of the data being used on the train and test errors.
It would be a great help if anyone could tell me why is this the case.
machine-learning training
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
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add a comment |
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I was reading about Adaboost Alogorithm and learned that if initially we split the dataset equally for training and testing, apply the algorithm. And then gradually start increasing the size of train dataset (and lower the test set) for each iteration of the algorithm , the difference between the training error and test error starts decreasing.
I wanted to understand the reason behind this and also the impact of the size of the data being used on the train and test errors.
It would be a great help if anyone could tell me why is this the case.
machine-learning training
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
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$begingroup$
Possible duplicate of Does Dataset training and test size affect algorithm?
$endgroup$
– Tasos
2 hours ago
add a comment |
$begingroup$
I was reading about Adaboost Alogorithm and learned that if initially we split the dataset equally for training and testing, apply the algorithm. And then gradually start increasing the size of train dataset (and lower the test set) for each iteration of the algorithm , the difference between the training error and test error starts decreasing.
I wanted to understand the reason behind this and also the impact of the size of the data being used on the train and test errors.
It would be a great help if anyone could tell me why is this the case.
machine-learning training
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
$endgroup$
I was reading about Adaboost Alogorithm and learned that if initially we split the dataset equally for training and testing, apply the algorithm. And then gradually start increasing the size of train dataset (and lower the test set) for each iteration of the algorithm , the difference between the training error and test error starts decreasing.
I wanted to understand the reason behind this and also the impact of the size of the data being used on the train and test errors.
It would be a great help if anyone could tell me why is this the case.
machine-learning training
machine-learning training
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
asked 4 hours ago
Shekhar TanwarShekhar Tanwar
61
61
$begingroup$
Possible duplicate of Does Dataset training and test size affect algorithm?
$endgroup$
– Tasos
2 hours ago
add a comment |
$begingroup$
Possible duplicate of Does Dataset training and test size affect algorithm?
$endgroup$
– Tasos
2 hours ago
$begingroup$
Possible duplicate of Does Dataset training and test size affect algorithm?
$endgroup$
– Tasos
2 hours ago
$begingroup$
Possible duplicate of Does Dataset training and test size affect algorithm?
$endgroup$
– Tasos
2 hours ago
add a comment |
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$begingroup$
Possible duplicate of Does Dataset training and test size affect algorithm?
$endgroup$
– Tasos
2 hours ago