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It would seem an answer can be given by quoting the two comments.

nikienikie:

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyerrcollyer:

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

It would seem an answer can be given by quoting the two comments.

nikie:

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyer:

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

It would seem an answer can be given by quoting the two comments.

nikie:

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyer:

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

2 added 334 characters in body
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It would seem an answer can be given by quoting the two comments.

nikienikie:

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyerrcollyer:

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

It would seem an answer can be given by quoting the two comments.

nikie

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyer

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

It would seem an answer can be given by quoting the two comments.

nikie:

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyer:

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

1
source | link

It would seem an answer can be given by quoting the two comments.

nikie

$\qquad $I'm guessing that Automatic actually tries multiple classifiers and chooses the best one, according to some criteria. And since some learners like random forests and neural networks aren't deterministic, that could lead to different results.

rcollyer

$\qquad $nikie's correct. Classify and Predict will randomly choose a method from a weighted list that is determined by your data. So, if your data changes in some significant way (size, type, etc.), the possible methods change. The only way to get a consistent result is to use SeedRandom which is true of any random process, or to specify the method yourself.

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