Scikit learn train test split without mixing participants in trails
0
$begingroup$
I have dataset of trails. There are 90 participants that appear in 90 trails each. So 450 trails in total.
I'm looking to split my dataset so participants doesn't get mixed over training and test set. I want all trails of 25 participants in my training set and trails of the remaining 25 in the test set.
The reason is I want to test on totally unseen data to access overfitting. Is there a way of achieving this within scikit-learn?
machine-learning
edited 14 hours ago
Simon Larsson
5086
asked yesterday
AndrewAndrew
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
0
$begingroup$
I have dataset of trails. There are 90 participants that appear in 90 trails each. So 450 trails in total.
I'm looking to split my dataset so participants doesn't get mixed over training and test set. I want all trails of 25 participants in my training set and trails of the remaining 25 in the test set.
The reason is I want to test on totally unseen data to access overfitting. Is there a way of achieving this within scikit-learn?
machine-learning
edited 14 hours ago
Simon Larsson
5086
asked yesterday
AndrewAndrew
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
What do you mean by "splitting based on participant?"
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan As in, I would like to split based on participant IDs and then classify exercises. For example, if I wanted to do a 50/50 train/test split, then I would have 25 participants data in the training, then test on the other 25 participants data.
$endgroup$
– Andrew
yesterday
$begingroup$
I tried editing to clear up some of the confusion about what you are asking. Maybe someone will be able to answer now, but I'm pretty sure it would be easier to implement this functionality yourself.
$endgroup$
– Simon Larsson
14 hours ago
add a comment |
0
0
0
$begingroup$
I have dataset of trails. There are 90 participants that appear in 90 trails each. So 450 trails in total.
I'm looking to split my dataset so participants doesn't get mixed over training and test set. I want all trails of 25 participants in my training set and trails of the remaining 25 in the test set.
The reason is I want to test on totally unseen data to access overfitting. Is there a way of achieving this within scikit-learn?
machine-learning
edited 14 hours ago
Simon Larsson
5086
asked yesterday
AndrewAndrew
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have dataset of trails. There are 90 participants that appear in 90 trails each. So 450 trails in total.
I'm looking to split my dataset so participants doesn't get mixed over training and test set. I want all trails of 25 participants in my training set and trails of the remaining 25 in the test set.
The reason is I want to test on totally unseen data to access overfitting. Is there a way of achieving this within scikit-learn?
machine-learning
machine-learning
edited 14 hours ago
Simon Larsson
5086
asked yesterday
AndrewAndrew
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 14 hours ago
Simon Larsson
5086
asked yesterday
AndrewAndrew
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 14 hours ago
Simon Larsson
5086
edited 14 hours ago
Simon Larsson
5086
edited 14 hours ago
Simon Larsson
5086
5086
asked yesterday
AndrewAndrew
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
AndrewAndrew
1
asked yesterday
AndrewAndrew
1
1
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Andrew is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
What do you mean by "splitting based on participant?"
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan As in, I would like to split based on participant IDs and then classify exercises. For example, if I wanted to do a 50/50 train/test split, then I would have 25 participants data in the training, then test on the other 25 participants data.
$endgroup$
– Andrew
yesterday
$begingroup$
I tried editing to clear up some of the confusion about what you are asking. Maybe someone will be able to answer now, but I'm pretty sure it would be easier to implement this functionality yourself.
$endgroup$
– Simon Larsson
14 hours ago
add a comment |
$begingroup$
What do you mean by "splitting based on participant?"
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan As in, I would like to split based on participant IDs and then classify exercises. For example, if I wanted to do a 50/50 train/test split, then I would have 25 participants data in the training, then test on the other 25 participants data.
$endgroup$
– Andrew
yesterday
$begingroup$
I tried editing to clear up some of the confusion about what you are asking. Maybe someone will be able to answer now, but I'm pretty sure it would be easier to implement this functionality yourself.
$endgroup$
– Simon Larsson
14 hours ago
$begingroup$
What do you mean by "splitting based on participant?"
$endgroup$
– Ethan
yesterday
$begingroup$
What do you mean by "splitting based on participant?"
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan As in, I would like to split based on participant IDs and then classify exercises. For example, if I wanted to do a 50/50 train/test split, then I would have 25 participants data in the training, then test on the other 25 participants data.
$endgroup$
– Andrew
yesterday
$begingroup$
@Ethan As in, I would like to split based on participant IDs and then classify exercises. For example, if I wanted to do a 50/50 train/test split, then I would have 25 participants data in the training, then test on the other 25 participants data.
$endgroup$
– Andrew
yesterday
$begingroup$
I tried editing to clear up some of the confusion about what you are asking. Maybe someone will be able to answer now, but I'm pretty sure it would be easier to implement this functionality yourself.
$endgroup$
– Simon Larsson
14 hours ago
$begingroup$
I tried editing to clear up some of the confusion about what you are asking. Maybe someone will be able to answer now, but I'm pretty sure it would be easier to implement this functionality yourself.
$endgroup$
– Simon Larsson
14 hours ago
add a comment |
1 Answer
1
active
oldest
votes
2
$begingroup$
To split data into Training and Test sets in scikit-learn you can use the train_test_split function.
To implement this:
from sklearn.model_selection import train_test_split
sklearn.model_selection.train_test_split()
Then pass through the arguments that you would like to set as parameters. Some parameters of note you may like to tune are the sizes of the training and test sets as well as setting if the splits are shuffled or not.
You can read about this further on its scikit-learn documentation page here.
answered yesterday
EthanEthan
580222
$endgroup$
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
|
show 4 more comments
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1 Answer
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2
$begingroup$
To split data into Training and Test sets in scikit-learn you can use the train_test_split function.
To implement this:
from sklearn.model_selection import train_test_split
sklearn.model_selection.train_test_split()
Then pass through the arguments that you would like to set as parameters. Some parameters of note you may like to tune are the sizes of the training and test sets as well as setting if the splits are shuffled or not.
You can read about this further on its scikit-learn documentation page here.
answered yesterday
EthanEthan
580222
$endgroup$
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
|
show 4 more comments
2
$begingroup$
To split data into Training and Test sets in scikit-learn you can use the train_test_split function.
To implement this:
from sklearn.model_selection import train_test_split
sklearn.model_selection.train_test_split()
Then pass through the arguments that you would like to set as parameters. Some parameters of note you may like to tune are the sizes of the training and test sets as well as setting if the splits are shuffled or not.
You can read about this further on its scikit-learn documentation page here.
answered yesterday
EthanEthan
580222
$endgroup$
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
|
show 4 more comments
2
2
2
$begingroup$
To split data into Training and Test sets in scikit-learn you can use the train_test_split function.
To implement this:
from sklearn.model_selection import train_test_split
sklearn.model_selection.train_test_split()
Then pass through the arguments that you would like to set as parameters. Some parameters of note you may like to tune are the sizes of the training and test sets as well as setting if the splits are shuffled or not.
You can read about this further on its scikit-learn documentation page here.
answered yesterday
EthanEthan
580222
$endgroup$
To split data into Training and Test sets in scikit-learn you can use the train_test_split function.
To implement this:
from sklearn.model_selection import train_test_split
sklearn.model_selection.train_test_split()
Then pass through the arguments that you would like to set as parameters. Some parameters of note you may like to tune are the sizes of the training and test sets as well as setting if the splits are shuffled or not.
You can read about this further on its scikit-learn documentation page here.
answered yesterday
EthanEthan
580222
answered yesterday
EthanEthan
580222
answered yesterday
EthanEthan
580222
answered yesterday
EthanEthan
580222
580222
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
|
show 4 more comments
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
Yes, I am using that function. I don't think stratify is the correct parameter since all that is doing it looking to make sure proportions stay the same. I just want to split participant data as being used for training only or testing only.
$endgroup$
– Andrew
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
train_test_split will by default, do a 75% training 25% testing split. Is this what you want to change? I am not sure I understand your question.
$endgroup$
– Ethan
yesterday
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
No, I want to split based on participants. Currently it randomly splits so all 50 participants are very likely going to be included in the training and testing portions.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
I want to do a 50% train split with the additional parameter that participants are mutually excluded to either the train or test split. So there are 25 participants worth of data on the train side and 25 participants worth of data on the test side. Basically, is there an easy way to randomize 50 participants into two groups? It seems like the answer is no and requires a custom script.
$endgroup$
– Andrew
23 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
$begingroup$
What exactly do you mean by very likely to be included? If you have 50 samples, and pass them through train_test_split, all 50 samples will be included in either the training set or the test set. To your second comment, everything is mutually exclusive. No sample will be included in both the training and the test set.
$endgroup$
– Ethan
11 hours ago
|
show 4 more comments
Andrew is a new contributor. Be nice, and check out our Code of Conduct.
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Andrew is a new contributor. Be nice, and check out our Code of Conduct.
Andrew is a new contributor. Be nice, and check out our Code of Conduct.
Andrew is a new contributor. Be nice, and check out our Code of Conduct.
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$begingroup$
What do you mean by "splitting based on participant?"
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan As in, I would like to split based on participant IDs and then classify exercises. For example, if I wanted to do a 50/50 train/test split, then I would have 25 participants data in the training, then test on the other 25 participants data.
$endgroup$
– Andrew
yesterday
$begingroup$
I tried editing to clear up some of the confusion about what you are asking. Maybe someone will be able to answer now, but I'm pretty sure it would be easier to implement this functionality yourself.
$endgroup$
– Simon Larsson
14 hours ago