Creating models for each group in dataframe column in R
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I would like to create a naiveBayes model per group of values of column TN.
Here is the code:
library(party)
airq <- subset(airquality, !is.na(Ozone))
ct <- ctree(Ozone ~ ., data = airq, controls = ctree_control(maxsurrogate = 3))
airq$TN<-factor (ct@where)
Here is an example:
> tail (airq)
Ozone Solar.R Wind Temp Month Day TN
1 7 49 10.3 69 9 24 2
2 14 20 16.6 63 9 25 5
3 30 193 6.9 70 9 26 3
4 14 191 14.3 75 9 28 2
5 18 131 8.0 76 9 29 5
6 20 223 11.5 68 9 30 3
I want to build a NaiveBayes model per value:
model[i] <- naiveBayes(Ozone ~ ., data = dat[i])
dat[1] will contain lines 1 and 4 (TN=2) for creating first model,dat[2] contains lines 2 and 5 for (TN=5) for the second model, dat[3] contains lines 3 and for third model (TN=3).
So finally, I'll be able to sum it up: for each unique group values in TN I'll have its model.
Like this:
TN_val model Based on Source_Lines
1 2 model[1] 1,4
2 5 model[2] 2,5
3 3 model[3] 3,6
r dataframe grouping naivebayes party
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
add a comment |
0
I would like to create a naiveBayes model per group of values of column TN.
Here is the code:
library(party)
airq <- subset(airquality, !is.na(Ozone))
ct <- ctree(Ozone ~ ., data = airq, controls = ctree_control(maxsurrogate = 3))
airq$TN<-factor (ct@where)
Here is an example:
> tail (airq)
Ozone Solar.R Wind Temp Month Day TN
1 7 49 10.3 69 9 24 2
2 14 20 16.6 63 9 25 5
3 30 193 6.9 70 9 26 3
4 14 191 14.3 75 9 28 2
5 18 131 8.0 76 9 29 5
6 20 223 11.5 68 9 30 3
I want to build a NaiveBayes model per value:
model[i] <- naiveBayes(Ozone ~ ., data = dat[i])
dat[1] will contain lines 1 and 4 (TN=2) for creating first model,dat[2] contains lines 2 and 5 for (TN=5) for the second model, dat[3] contains lines 3 and for third model (TN=3).
So finally, I'll be able to sum it up: for each unique group values in TN I'll have its model.
Like this:
TN_val model Based on Source_Lines
1 2 model[1] 1,4
2 5 model[2] 2,5
3 3 model[3] 3,6
r dataframe grouping naivebayes party
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
1
lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x))
– LAP
Nov 23 '18 at 6:41
Hi @LAP, Thanks. How can I get the relevant value of TN per the model?
– Avi
Nov 23 '18 at 7:08
1
The name of the list element will be equal to the value of the TN for each model in the list. So if you'd usemymodels <- lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x)),names(mymodels)[1]would display the TN value of the first model.
– LAP
Nov 23 '18 at 7:16
Thanks again @LAP. One more question: I have an additional of airq dataframe (for testing). I would like to run (predict) the mymodels on the new data per line per TN value. How can I do it?
– Avi
Nov 23 '18 at 7:33
add a comment |
0
0
0
1
I would like to create a naiveBayes model per group of values of column TN.
Here is the code:
library(party)
airq <- subset(airquality, !is.na(Ozone))
ct <- ctree(Ozone ~ ., data = airq, controls = ctree_control(maxsurrogate = 3))
airq$TN<-factor (ct@where)
Here is an example:
> tail (airq)
Ozone Solar.R Wind Temp Month Day TN
1 7 49 10.3 69 9 24 2
2 14 20 16.6 63 9 25 5
3 30 193 6.9 70 9 26 3
4 14 191 14.3 75 9 28 2
5 18 131 8.0 76 9 29 5
6 20 223 11.5 68 9 30 3
I want to build a NaiveBayes model per value:
model[i] <- naiveBayes(Ozone ~ ., data = dat[i])
dat[1] will contain lines 1 and 4 (TN=2) for creating first model,dat[2] contains lines 2 and 5 for (TN=5) for the second model, dat[3] contains lines 3 and for third model (TN=3).
So finally, I'll be able to sum it up: for each unique group values in TN I'll have its model.
Like this:
TN_val model Based on Source_Lines
1 2 model[1] 1,4
2 5 model[2] 2,5
3 3 model[3] 3,6
r dataframe grouping naivebayes party
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
I would like to create a naiveBayes model per group of values of column TN.
Here is the code:
library(party)
airq <- subset(airquality, !is.na(Ozone))
ct <- ctree(Ozone ~ ., data = airq, controls = ctree_control(maxsurrogate = 3))
airq$TN<-factor (ct@where)
Here is an example:
> tail (airq)
Ozone Solar.R Wind Temp Month Day TN
1 7 49 10.3 69 9 24 2
2 14 20 16.6 63 9 25 5
3 30 193 6.9 70 9 26 3
4 14 191 14.3 75 9 28 2
5 18 131 8.0 76 9 29 5
6 20 223 11.5 68 9 30 3
I want to build a NaiveBayes model per value:
model[i] <- naiveBayes(Ozone ~ ., data = dat[i])
dat[1] will contain lines 1 and 4 (TN=2) for creating first model,dat[2] contains lines 2 and 5 for (TN=5) for the second model, dat[3] contains lines 3 and for third model (TN=3).
So finally, I'll be able to sum it up: for each unique group values in TN I'll have its model.
Like this:
TN_val model Based on Source_Lines
1 2 model[1] 1,4
2 5 model[2] 2,5
3 3 model[3] 3,6
r dataframe grouping naivebayes party
r dataframe grouping naivebayes party
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
asked Nov 23 '18 at 6:36
AviAvi
1,03111734
1,03111734
1
lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x))
– LAP
Nov 23 '18 at 6:41
Hi @LAP, Thanks. How can I get the relevant value of TN per the model?
– Avi
Nov 23 '18 at 7:08
1
The name of the list element will be equal to the value of the TN for each model in the list. So if you'd usemymodels <- lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x)),names(mymodels)[1]would display the TN value of the first model.
– LAP
Nov 23 '18 at 7:16
Thanks again @LAP. One more question: I have an additional of airq dataframe (for testing). I would like to run (predict) the mymodels on the new data per line per TN value. How can I do it?
– Avi
Nov 23 '18 at 7:33
add a comment |
1
lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x))
– LAP
Nov 23 '18 at 6:41
Hi @LAP, Thanks. How can I get the relevant value of TN per the model?
– Avi
Nov 23 '18 at 7:08
1
The name of the list element will be equal to the value of the TN for each model in the list. So if you'd usemymodels <- lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x)),names(mymodels)[1]would display the TN value of the first model.
– LAP
Nov 23 '18 at 7:16
Thanks again @LAP. One more question: I have an additional of airq dataframe (for testing). I would like to run (predict) the mymodels on the new data per line per TN value. How can I do it?
– Avi
Nov 23 '18 at 7:33
1
1
lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x))– LAP
Nov 23 '18 at 6:41
lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x))– LAP
Nov 23 '18 at 6:41
Hi @LAP, Thanks. How can I get the relevant value of TN per the model?
– Avi
Nov 23 '18 at 7:08
Hi @LAP, Thanks. How can I get the relevant value of TN per the model?
– Avi
Nov 23 '18 at 7:08
1
1
The name of the list element will be equal to the value of the TN for each model in the list. So if you'd use
mymodels <- lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x)), names(mymodels)[1] would display the TN value of the first model.– LAP
Nov 23 '18 at 7:16
The name of the list element will be equal to the value of the TN for each model in the list. So if you'd use
mymodels <- lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x)), names(mymodels)[1] would display the TN value of the first model.– LAP
Nov 23 '18 at 7:16
Thanks again @LAP. One more question: I have an additional of airq dataframe (for testing). I would like to run (predict) the mymodels on the new data per line per TN value. How can I do it?
– Avi
Nov 23 '18 at 7:33
Thanks again @LAP. One more question: I have an additional of airq dataframe (for testing). I would like to run (predict) the mymodels on the new data per line per TN value. How can I do it?
– Avi
Nov 23 '18 at 7:33
add a comment |
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1
lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x))– LAP
Nov 23 '18 at 6:41
Hi @LAP, Thanks. How can I get the relevant value of TN per the model?
– Avi
Nov 23 '18 at 7:08
1
The name of the list element will be equal to the value of the TN for each model in the list. So if you'd use
mymodels <- lapply(split(airq, airq$TN), function(x) naiveBayes(Ozone ~ ., data = x)),names(mymodels)[1]would display the TN value of the first model.– LAP
Nov 23 '18 at 7:16
Thanks again @LAP. One more question: I have an additional of airq dataframe (for testing). I would like to run (predict) the mymodels on the new data per line per TN value. How can I do it?
– Avi
Nov 23 '18 at 7:33