Dealing with a dataset with a mix of continuous and categorical variables Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern) 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsDetermine highly correlated segmentsHow to visualize (make plot) of regression output against categorical input variable?Imputation of missing values and dealing with categorical valuesPreparing, Scaling and Selecting from a combination of numerical and categorical featuresWhat approach for creating a multi-classification model based on all categorical features (1 with 5,000 levels)?Catboost Categorical Features Handling Options (CTR settings)?How to combine categorical and continuous input features for neural network trainingExplaination of the anomalies detectedHow to do multivariate survival analysis on dataset having only categorical variables
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Dealing with a dataset with a mix of continuous and categorical variables
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsDetermine highly correlated segmentsHow to visualize (make plot) of regression output against categorical input variable?Imputation of missing values and dealing with categorical valuesPreparing, Scaling and Selecting from a combination of numerical and categorical featuresWhat approach for creating a multi-classification model based on all categorical features (1 with 5,000 levels)?Catboost Categorical Features Handling Options (CTR settings)?How to combine categorical and continuous input features for neural network trainingExplaination of the anomalies detectedHow to do multivariate survival analysis on dataset having only categorical variables
$begingroup$
How do the choice of machine learning algorithm and preprocessing change when some of the independent variables are categorical while others are continuous? Can such data be directly applied to the algorithm with categorical data converted using one-hot encoding?
For example, 2 columns are: Age and Race, Age being continuous and Race is categorical.
Update: Ideal buckets for a continuous variable is not known.
machine-learning data-cleaning categorical-data
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
$endgroup$
add a comment |
$begingroup$
How do the choice of machine learning algorithm and preprocessing change when some of the independent variables are categorical while others are continuous? Can such data be directly applied to the algorithm with categorical data converted using one-hot encoding?
For example, 2 columns are: Age and Race, Age being continuous and Race is categorical.
Update: Ideal buckets for a continuous variable is not known.
machine-learning data-cleaning categorical-data
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
$endgroup$
add a comment |
$begingroup$
How do the choice of machine learning algorithm and preprocessing change when some of the independent variables are categorical while others are continuous? Can such data be directly applied to the algorithm with categorical data converted using one-hot encoding?
For example, 2 columns are: Age and Race, Age being continuous and Race is categorical.
Update: Ideal buckets for a continuous variable is not known.
machine-learning data-cleaning categorical-data
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
$endgroup$
How do the choice of machine learning algorithm and preprocessing change when some of the independent variables are categorical while others are continuous? Can such data be directly applied to the algorithm with categorical data converted using one-hot encoding?
For example, 2 columns are: Age and Race, Age being continuous and Race is categorical.
Update: Ideal buckets for a continuous variable is not known.
machine-learning data-cleaning categorical-data
machine-learning data-cleaning categorical-data
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
edited Mar 4 at 6:46
Jibin Mathew
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
asked Feb 22 at 7:53
Jibin MathewJibin Mathew
1345
1345
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
To clarify, you mean mixed variables in one column? e.g. ABC123
If yes, you create two additional columns: one with categorical and one with numerical values. Afterward, you can encode them (one hot encoding not always necessary).
Detailed explanation in Chapter 11 "Feature Engineering Mixed Variables":
https://www.udemy.com/feature-engineering-for-machine-learning/learn/v4/content
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
$endgroup$
add a comment |
$begingroup$
One approach would be to "split" the continuous variable in buckets. Say, for age - 0-18yrs, 18-65yrs; 65+ yrs.
Then, you could assign the input age to a bucket and threat it as a categorical variable.
answered Feb 28 at 20:40
stan0stan0
1012
$endgroup$
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
To clarify, you mean mixed variables in one column? e.g. ABC123
If yes, you create two additional columns: one with categorical and one with numerical values. Afterward, you can encode them (one hot encoding not always necessary).
Detailed explanation in Chapter 11 "Feature Engineering Mixed Variables":
https://www.udemy.com/feature-engineering-for-machine-learning/learn/v4/content
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
$endgroup$
add a comment |
$begingroup$
To clarify, you mean mixed variables in one column? e.g. ABC123
If yes, you create two additional columns: one with categorical and one with numerical values. Afterward, you can encode them (one hot encoding not always necessary).
Detailed explanation in Chapter 11 "Feature Engineering Mixed Variables":
https://www.udemy.com/feature-engineering-for-machine-learning/learn/v4/content
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
$endgroup$
add a comment |
$begingroup$
To clarify, you mean mixed variables in one column? e.g. ABC123
If yes, you create two additional columns: one with categorical and one with numerical values. Afterward, you can encode them (one hot encoding not always necessary).
Detailed explanation in Chapter 11 "Feature Engineering Mixed Variables":
https://www.udemy.com/feature-engineering-for-machine-learning/learn/v4/content
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
$endgroup$
To clarify, you mean mixed variables in one column? e.g. ABC123
If yes, you create two additional columns: one with categorical and one with numerical values. Afterward, you can encode them (one hot encoding not always necessary).
Detailed explanation in Chapter 11 "Feature Engineering Mixed Variables":
https://www.udemy.com/feature-engineering-for-machine-learning/learn/v4/content
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
answered Feb 22 at 21:03
FrancoSwissFrancoSwiss
10115
10115
add a comment |
add a comment |
$begingroup$
One approach would be to "split" the continuous variable in buckets. Say, for age - 0-18yrs, 18-65yrs; 65+ yrs.
Then, you could assign the input age to a bucket and threat it as a categorical variable.
answered Feb 28 at 20:40
stan0stan0
1012
$endgroup$
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
add a comment |
$begingroup$
One approach would be to "split" the continuous variable in buckets. Say, for age - 0-18yrs, 18-65yrs; 65+ yrs.
Then, you could assign the input age to a bucket and threat it as a categorical variable.
answered Feb 28 at 20:40
stan0stan0
1012
$endgroup$
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
add a comment |
$begingroup$
One approach would be to "split" the continuous variable in buckets. Say, for age - 0-18yrs, 18-65yrs; 65+ yrs.
Then, you could assign the input age to a bucket and threat it as a categorical variable.
answered Feb 28 at 20:40
stan0stan0
1012
$endgroup$
One approach would be to "split" the continuous variable in buckets. Say, for age - 0-18yrs, 18-65yrs; 65+ yrs.
Then, you could assign the input age to a bucket and threat it as a categorical variable.
answered Feb 28 at 20:40
stan0stan0
1012
answered Feb 28 at 20:40
stan0stan0
1012
answered Feb 28 at 20:40
stan0stan0
1012
answered Feb 28 at 20:40
stan0stan0
1012
1012
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
add a comment |
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
$begingroup$
The question doesn't even focus on what you answered for!
$endgroup$
– Jibin Mathew
Mar 4 at 6:48
add a comment |
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