Is there an algorithm that imputes missing values based on n nearest columns? (KNN hybrid) The 2019 Stack Overflow Developer Survey Results Are In 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 ResultsWhere in the workflow should we deal with missing data?Assigning values to missing target vector values in scikit-learnImputation of missing values and dealing with categorical valuesIs there a way to standardize latitude and longitude to be used as predictors in KNN algorithm?Is there are way to impute missing values by clustering, regression and stochastic regressionIs there an upper bound for k in nearest neighbors-based methods?How does KNN work if there are duplicates?How to select variables based on the mean correlation in a correlation matrix?Multiple filtering pandas columns based on values in another columnHow to create a df that gets sum of columns based on a groupby column?
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Is there an algorithm that imputes missing values based on n nearest columns? (KNN hybrid)
The 2019 Stack Overflow Developer Survey Results Are In
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 ResultsWhere in the workflow should we deal with missing data?Assigning values to missing target vector values in scikit-learnImputation of missing values and dealing with categorical valuesIs there a way to standardize latitude and longitude to be used as predictors in KNN algorithm?Is there are way to impute missing values by clustering, regression and stochastic regressionIs there an upper bound for k in nearest neighbors-based methods?How does KNN work if there are duplicates?How to select variables based on the mean correlation in a correlation matrix?Multiple filtering pandas columns based on values in another columnHow to create a df that gets sum of columns based on a groupby column?
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I have a dataset of 70 columns that have missing values. Each column has a few columns (3-5) that it is significantly more correlated than the others but each column's correlated columns are very different from other columns. I would like to perform a tweaked version of KNN imputation and before I start writing this from scratch, I'd like to know if there's something similar out there so I don't go about reinventing the wheel.
On initialisation, a correlation matrix is obtained between all the variables. For every missing cell that needs to be imputed, the algorithm retrieves from the correlation matrix the top n highest correlated columns and uses only those n columns to select the k nearest neighbours and use the mean value of those neighbours.
Thanks and apologies if I am not very clear with my question. I'll try to clarify if you have any doubts.
python k-nn
asked 18 mins ago
JoshuaJoshua
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add a comment |
$begingroup$
I have a dataset of 70 columns that have missing values. Each column has a few columns (3-5) that it is significantly more correlated than the others but each column's correlated columns are very different from other columns. I would like to perform a tweaked version of KNN imputation and before I start writing this from scratch, I'd like to know if there's something similar out there so I don't go about reinventing the wheel.
On initialisation, a correlation matrix is obtained between all the variables. For every missing cell that needs to be imputed, the algorithm retrieves from the correlation matrix the top n highest correlated columns and uses only those n columns to select the k nearest neighbours and use the mean value of those neighbours.
Thanks and apologies if I am not very clear with my question. I'll try to clarify if you have any doubts.
python k-nn
asked 18 mins ago
JoshuaJoshua
1
New contributor
Joshua 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 |
$begingroup$
I have a dataset of 70 columns that have missing values. Each column has a few columns (3-5) that it is significantly more correlated than the others but each column's correlated columns are very different from other columns. I would like to perform a tweaked version of KNN imputation and before I start writing this from scratch, I'd like to know if there's something similar out there so I don't go about reinventing the wheel.
On initialisation, a correlation matrix is obtained between all the variables. For every missing cell that needs to be imputed, the algorithm retrieves from the correlation matrix the top n highest correlated columns and uses only those n columns to select the k nearest neighbours and use the mean value of those neighbours.
Thanks and apologies if I am not very clear with my question. I'll try to clarify if you have any doubts.
python k-nn
asked 18 mins ago
JoshuaJoshua
1
New contributor
Joshua 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 a dataset of 70 columns that have missing values. Each column has a few columns (3-5) that it is significantly more correlated than the others but each column's correlated columns are very different from other columns. I would like to perform a tweaked version of KNN imputation and before I start writing this from scratch, I'd like to know if there's something similar out there so I don't go about reinventing the wheel.
On initialisation, a correlation matrix is obtained between all the variables. For every missing cell that needs to be imputed, the algorithm retrieves from the correlation matrix the top n highest correlated columns and uses only those n columns to select the k nearest neighbours and use the mean value of those neighbours.
Thanks and apologies if I am not very clear with my question. I'll try to clarify if you have any doubts.
python k-nn
python k-nn
asked 18 mins ago
JoshuaJoshua
1
New contributor
Joshua is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 18 mins ago
JoshuaJoshua
1
New contributor
Joshua is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 18 mins ago
JoshuaJoshua
1
New contributor
Joshua is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 18 mins ago
JoshuaJoshua
1
asked 18 mins ago
JoshuaJoshua
1
1
New contributor
Joshua is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Joshua is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Joshua is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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