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edit approved Aug 10, 2015 at 8:40
Dawny33
edit approved Aug 10, 2015 at 8:40
Dawny33
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After reading some material, I found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/moving window of train set.
  3. Leave a relatively small (warming) period between test and train sets, and then use window again (including the warming period).

What should be the most accurate way for applying machine learning algorithms and parameters estimation? Thanks in advance!

After reading some material, I found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/moving window of train set.
  3. Leave a relatively small (warming) period between test and train sets, and then use window again (including the warming period).

What should be the most accurate way for applying machine learning algorithms and parameters estimation? Thanks in advance!

After reading some material, I found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/moving window of train set.
  3. Leave a relatively small (warming) period between test and train sets, and then use window again (including the warming period).

What should be the most accurate way for applying machine learning algorithms and parameters estimation?

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Nick Stauner
Nick Stauner
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How to define train and test sets in financial time series for estimating Machine Learningmachine learning parameters

afterAfter reading some material i, I found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/Movingmoving window of train set.
  3. leaveLeave a relatively small (warming) period between test and train sets, and then use window again (including the warming period).

What should be the most accurate way for applying Machine Learningmachine learning algorithms and parameters estimation.? Thanks in advance!

How to define train and test sets in financial time series for estimating Machine Learning parameters

after reading some material i found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/Moving window of train set.
  3. leave a relatively small (warming) period between test and train sets and then use window again (including the warming period).

What should be the most accurate way for applying Machine Learning algorithms and parameters estimation. Thanks in advance!

How to define train and test sets in financial time series for estimating machine learning parameters

After reading some material, I found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/moving window of train set.
  3. Leave a relatively small (warming) period between test and train sets, and then use window again (including the warming period).

What should be the most accurate way for applying machine learning algorithms and parameters estimation? Thanks in advance!

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Eitan
Eitan
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How to define train and test sets in financial time series for estimating Machine Learning parameters

after reading some material i found few options for defining train and test sets:

  1. Just splitting with no change.
  2. Accumulating/Moving window of train set.
  3. leave a relatively small (warming) period between test and train sets and then use window again (including the warming period).

What should be the most accurate way for applying Machine Learning algorithms and parameters estimation. Thanks in advance!