Use of h2o cluster for Neural Network Model
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I'm trying to fit an ANN model to a dataset having 7 predictor variables and the response variable is a binary.
I have converted all the required factor variables to numeric (If I am correct, this is a requirement) and the following error pops up?
In .h2o.startModelJob(algo, params, h2oRestApiVersion) :
Dropping bad and constant columns: [Month, Day of Month, Day Of Week].
Please suggest a way out.
Thanks,
SK
r neural-network artificial-intelligence cluster-computing h2o
asked Nov 21 at 23:40
srkale
92
add a comment |
up vote
0
down vote
favorite
I'm trying to fit an ANN model to a dataset having 7 predictor variables and the response variable is a binary.
I have converted all the required factor variables to numeric (If I am correct, this is a requirement) and the following error pops up?
In .h2o.startModelJob(algo, params, h2oRestApiVersion) :
Dropping bad and constant columns: [Month, Day of Month, Day Of Week].
Please suggest a way out.
Thanks,
SK
r neural-network artificial-intelligence cluster-computing h2o
asked Nov 21 at 23:40
srkale
92
Are you able to fit any other simple model on your data? Say, a simpleglm? If not, then check whether you transformfactorstonumericcorrectly. One way is throughmodel.matrix()
– Nutle
Nov 22 at 15:27
Okay. I'll check if I can do that. Thanks
– srkale
Nov 22 at 16:41
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I'm trying to fit an ANN model to a dataset having 7 predictor variables and the response variable is a binary.
I have converted all the required factor variables to numeric (If I am correct, this is a requirement) and the following error pops up?
In .h2o.startModelJob(algo, params, h2oRestApiVersion) :
Dropping bad and constant columns: [Month, Day of Month, Day Of Week].
Please suggest a way out.
Thanks,
SK
r neural-network artificial-intelligence cluster-computing h2o
asked Nov 21 at 23:40
srkale
92
I'm trying to fit an ANN model to a dataset having 7 predictor variables and the response variable is a binary.
I have converted all the required factor variables to numeric (If I am correct, this is a requirement) and the following error pops up?
In .h2o.startModelJob(algo, params, h2oRestApiVersion) :
Dropping bad and constant columns: [Month, Day of Month, Day Of Week].
Please suggest a way out.
Thanks,
SK
r neural-network artificial-intelligence cluster-computing h2o
r neural-network artificial-intelligence cluster-computing h2o
asked Nov 21 at 23:40
srkale
92
asked Nov 21 at 23:40
srkale
92
asked Nov 21 at 23:40
srkale
92
asked Nov 21 at 23:40
srkale
92
asked Nov 21 at 23:40
srkale
92
92
Are you able to fit any other simple model on your data? Say, a simpleglm? If not, then check whether you transformfactorstonumericcorrectly. One way is throughmodel.matrix()
– Nutle
Nov 22 at 15:27
Okay. I'll check if I can do that. Thanks
– srkale
Nov 22 at 16:41
add a comment |
Are you able to fit any other simple model on your data? Say, a simpleglm? If not, then check whether you transformfactorstonumericcorrectly. One way is throughmodel.matrix()
– Nutle
Nov 22 at 15:27
Okay. I'll check if I can do that. Thanks
– srkale
Nov 22 at 16:41
Are you able to fit any other simple model on your data? Say, a simple
glm? If not, then check whether you transform factors to numeric correctly. One way is through model.matrix()– Nutle
Nov 22 at 15:27
Are you able to fit any other simple model on your data? Say, a simple
glm? If not, then check whether you transform factors to numeric correctly. One way is through model.matrix()– Nutle
Nov 22 at 15:27
Okay. I'll check if I can do that. Thanks
– srkale
Nov 22 at 16:41
Okay. I'll check if I can do that. Thanks
– srkale
Nov 22 at 16:41
add a comment |
1 Answer
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The message about dropping constant columns is not an error. It is just telling you the model identified that those columns will not impact the predictions and so those columns will be ignored.
answered Nov 22 at 21:58
TomKraljevic
2,097613
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
add a comment |
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1 Answer
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active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
The message about dropping constant columns is not an error. It is just telling you the model identified that those columns will not impact the predictions and so those columns will be ignored.
answered Nov 22 at 21:58
TomKraljevic
2,097613
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
add a comment |
up vote
0
down vote
The message about dropping constant columns is not an error. It is just telling you the model identified that those columns will not impact the predictions and so those columns will be ignored.
answered Nov 22 at 21:58
TomKraljevic
2,097613
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
add a comment |
up vote
0
down vote
up vote
0
down vote
The message about dropping constant columns is not an error. It is just telling you the model identified that those columns will not impact the predictions and so those columns will be ignored.
answered Nov 22 at 21:58
TomKraljevic
2,097613
The message about dropping constant columns is not an error. It is just telling you the model identified that those columns will not impact the predictions and so those columns will be ignored.
answered Nov 22 at 21:58
TomKraljevic
2,097613
answered Nov 22 at 21:58
TomKraljevic
2,097613
answered Nov 22 at 21:58
TomKraljevic
2,097613
answered Nov 22 at 21:58
TomKraljevic
2,097613
2,097613
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
add a comment |
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Okay. Thanks for the answer. I have another question, can categorical variables be used in this type of a model?
– srkale
Nov 24 at 14:24
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
Yes, h2o-3 can use categorical columns as inputs for a model.
– TomKraljevic
Nov 24 at 17:16
add a comment |
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Are you able to fit any other simple model on your data? Say, a simple
glm? If not, then check whether you transformfactorstonumericcorrectly. One way is throughmodel.matrix()– Nutle
Nov 22 at 15:27
Okay. I'll check if I can do that. Thanks
– srkale
Nov 22 at 16:41