does index of my data which is of type “Date time index” plays a part in reggression?Linearly increasing data with manual resetType of regression with nominal, ordinal, interval and ratio dataCan Machine Learning be applied in software developementClustering Crime Data which has latitute, longitude, crime-type tuplesDoes variation in data density over time affect regression models?Which type of regression has the best predictive power for extrapolating for smaller values?Time series prediction of discontinuous dataConvert Atypical Date Format for Time Series in PythonCan I use regression to solve a multiple equation problemMAE,MSE and MAPE aren't comparable?
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does index of my data which is of type “Date time index” plays a part in reggression?
Linearly increasing data with manual resetType of regression with nominal, ordinal, interval and ratio dataCan Machine Learning be applied in software developementClustering Crime Data which has latitute, longitude, crime-type tuplesDoes variation in data density over time affect regression models?Which type of regression has the best predictive power for extrapolating for smaller values?Time series prediction of discontinuous dataConvert Atypical Date Format for Time Series in PythonCan I use regression to solve a multiple equation problemMAE,MSE and MAPE aren't comparable?
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I'm new to data science and I'm working on a regression problem. My question is the index of my data which is of type "Date time index" plays a part in regression? I mean is it Okay if i drop the index ?
machine-learning data-mining regression pandas
$endgroup$
add a comment |
$begingroup$
I'm new to data science and I'm working on a regression problem. My question is the index of my data which is of type "Date time index" plays a part in regression? I mean is it Okay if i drop the index ?
machine-learning data-mining regression pandas
$endgroup$
$begingroup$
Please explain more about the problem you are trying to solve (features and target)
$endgroup$
– Alireza Zolanvari
yesterday
$begingroup$
i have hourly data of a smart grid and i want to predict hourly system load
$endgroup$
– imtiaz ul Hassan
yesterday
add a comment |
$begingroup$
I'm new to data science and I'm working on a regression problem. My question is the index of my data which is of type "Date time index" plays a part in regression? I mean is it Okay if i drop the index ?
machine-learning data-mining regression pandas
$endgroup$
I'm new to data science and I'm working on a regression problem. My question is the index of my data which is of type "Date time index" plays a part in regression? I mean is it Okay if i drop the index ?
machine-learning data-mining regression pandas
machine-learning data-mining regression pandas
asked yesterday
imtiaz ul Hassanimtiaz ul Hassan
133
133
$begingroup$
Please explain more about the problem you are trying to solve (features and target)
$endgroup$
– Alireza Zolanvari
yesterday
$begingroup$
i have hourly data of a smart grid and i want to predict hourly system load
$endgroup$
– imtiaz ul Hassan
yesterday
add a comment |
$begingroup$
Please explain more about the problem you are trying to solve (features and target)
$endgroup$
– Alireza Zolanvari
yesterday
$begingroup$
i have hourly data of a smart grid and i want to predict hourly system load
$endgroup$
– imtiaz ul Hassan
yesterday
$begingroup$
Please explain more about the problem you are trying to solve (features and target)
$endgroup$
– Alireza Zolanvari
yesterday
$begingroup$
Please explain more about the problem you are trying to solve (features and target)
$endgroup$
– Alireza Zolanvari
yesterday
$begingroup$
i have hourly data of a smart grid and i want to predict hourly system load
$endgroup$
– imtiaz ul Hassan
yesterday
$begingroup$
i have hourly data of a smart grid and i want to predict hourly system load
$endgroup$
– imtiaz ul Hassan
yesterday
add a comment |
1 Answer
1
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$begingroup$
You can take the date into account, but you should convert it into numeric value.
Suggestions:
1) Consider "datetime" package in python to change it to numeric, or some other techniques such as indexing with date-time, and converting the index value to numeric, float, etc. I don't have your exact case, so cannot say specifically.
or
2) If you have time series data, then in many cases ARMAX, ARIMAX, Seasonal ARIMAX models can do a really good job.
New contributor
$endgroup$
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
You can take the date into account, but you should convert it into numeric value.
Suggestions:
1) Consider "datetime" package in python to change it to numeric, or some other techniques such as indexing with date-time, and converting the index value to numeric, float, etc. I don't have your exact case, so cannot say specifically.
or
2) If you have time series data, then in many cases ARMAX, ARIMAX, Seasonal ARIMAX models can do a really good job.
New contributor
$endgroup$
add a comment |
$begingroup$
You can take the date into account, but you should convert it into numeric value.
Suggestions:
1) Consider "datetime" package in python to change it to numeric, or some other techniques such as indexing with date-time, and converting the index value to numeric, float, etc. I don't have your exact case, so cannot say specifically.
or
2) If you have time series data, then in many cases ARMAX, ARIMAX, Seasonal ARIMAX models can do a really good job.
New contributor
$endgroup$
add a comment |
$begingroup$
You can take the date into account, but you should convert it into numeric value.
Suggestions:
1) Consider "datetime" package in python to change it to numeric, or some other techniques such as indexing with date-time, and converting the index value to numeric, float, etc. I don't have your exact case, so cannot say specifically.
or
2) If you have time series data, then in many cases ARMAX, ARIMAX, Seasonal ARIMAX models can do a really good job.
New contributor
$endgroup$
You can take the date into account, but you should convert it into numeric value.
Suggestions:
1) Consider "datetime" package in python to change it to numeric, or some other techniques such as indexing with date-time, and converting the index value to numeric, float, etc. I don't have your exact case, so cannot say specifically.
or
2) If you have time series data, then in many cases ARMAX, ARIMAX, Seasonal ARIMAX models can do a really good job.
New contributor
New contributor
answered yesterday
Karen DanielyanKaren Danielyan
16
16
New contributor
New contributor
add a comment |
add a comment |
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$begingroup$
Please explain more about the problem you are trying to solve (features and target)
$endgroup$
– Alireza Zolanvari
yesterday
$begingroup$
i have hourly data of a smart grid and i want to predict hourly system load
$endgroup$
– imtiaz ul Hassan
yesterday