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Score Columns in Azure ML Studio
2019 Community Moderator ElectionImprove a regression model and feature selectionPrediction model for marketing to prospective customers (using pandas)Decision Tree generating leaves for only one caseSales Dataset to determine best model for predicting future salesUsing Pandas to_numeric() in Azure Machine Learning StudioInstead of one-hot encoding a categorical variable, could I profile the data and use the percentile value from it's cumulative density distribution?Create Custom Python Model in Azure ML Studio?Optimising Expensive FunctionsClassification of religions in Azure Machine Learning StudioWhen creating a classification model, should predictors with little correlation to the response variable be included in the model?
$begingroup$
So I have a data set I have successfully used to train a model, and have decent results. I am using a Two Class Boosted Decision tree for a Boolean output. So far so good.
I now want to analyze each column of my data set and remove any column that is not a meaningful influence on the outcome. I see statistics on columns in my data set:
But I don't see whether a column has a strong relationship with the output variable. Any clues?
predictive-modeling feature-selection azure-ml
$endgroup$
add a comment |
$begingroup$
So I have a data set I have successfully used to train a model, and have decent results. I am using a Two Class Boosted Decision tree for a Boolean output. So far so good.
I now want to analyze each column of my data set and remove any column that is not a meaningful influence on the outcome. I see statistics on columns in my data set:
But I don't see whether a column has a strong relationship with the output variable. Any clues?
predictive-modeling feature-selection azure-ml
$endgroup$
add a comment |
$begingroup$
So I have a data set I have successfully used to train a model, and have decent results. I am using a Two Class Boosted Decision tree for a Boolean output. So far so good.
I now want to analyze each column of my data set and remove any column that is not a meaningful influence on the outcome. I see statistics on columns in my data set:
But I don't see whether a column has a strong relationship with the output variable. Any clues?
predictive-modeling feature-selection azure-ml
$endgroup$
So I have a data set I have successfully used to train a model, and have decent results. I am using a Two Class Boosted Decision tree for a Boolean output. So far so good.
I now want to analyze each column of my data set and remove any column that is not a meaningful influence on the outcome. I see statistics on columns in my data set:
But I don't see whether a column has a strong relationship with the output variable. Any clues?
predictive-modeling feature-selection azure-ml
predictive-modeling feature-selection azure-ml
asked Mar 26 at 16:02
JonJon
1011
1011
add a comment |
add a comment |
1 Answer
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$begingroup$
Some very helpful articles walked me through how to use the feature selection modules in Azure ML Studio:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection
I used the "Filter Based Feature Selection" Module:

I added it to my training experiment and added input data.

I chose the feature I was training my model to predict.

After running the experiment I viewed the visualization of the Features:


Now I am using this to find which columns are valuable and which need some work.
$endgroup$
add a comment |
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1 Answer
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active
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1 Answer
1
active
oldest
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active
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$begingroup$
Some very helpful articles walked me through how to use the feature selection modules in Azure ML Studio:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection
I used the "Filter Based Feature Selection" Module:

I added it to my training experiment and added input data.

I chose the feature I was training my model to predict.

After running the experiment I viewed the visualization of the Features:


Now I am using this to find which columns are valuable and which need some work.
$endgroup$
add a comment |
$begingroup$
Some very helpful articles walked me through how to use the feature selection modules in Azure ML Studio:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection
I used the "Filter Based Feature Selection" Module:

I added it to my training experiment and added input data.

I chose the feature I was training my model to predict.

After running the experiment I viewed the visualization of the Features:


Now I am using this to find which columns are valuable and which need some work.
$endgroup$
add a comment |
$begingroup$
Some very helpful articles walked me through how to use the feature selection modules in Azure ML Studio:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection
I used the "Filter Based Feature Selection" Module:

I added it to my training experiment and added input data.

I chose the feature I was training my model to predict.

After running the experiment I viewed the visualization of the Features:


Now I am using this to find which columns are valuable and which need some work.
$endgroup$
Some very helpful articles walked me through how to use the feature selection modules in Azure ML Studio:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/filter-based-feature-selection
I used the "Filter Based Feature Selection" Module:

I added it to my training experiment and added input data.

I chose the feature I was training my model to predict.

After running the experiment I viewed the visualization of the Features:


Now I am using this to find which columns are valuable and which need some work.
answered Mar 26 at 16:28
JonJon
1011
1011
add a comment |
add a comment |
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