Low accuracy in classification
$begingroup$
I have a well defined data where i have cleaned up my data to final form which has 20 features mapping to a number between 1 to 100. Upto 5 features are enabled(value set to 1) for each row. The data looks something like below
Result|f1|f2|...f19|f20
45 |0 | 1|... 1 | 0
92 |0 | 0|... 1 | 1
I'm trying to build machine learning models that can give me good accuracy and preferably models which can handle warm_start since each iteration generates some data that i need to fit into existing build model.
below are 2 classifiers that i tried to set some baseline
randclf = RandomForestClassifier(n_estimators=50)
decclf = DecisionTreeClassifier(criterion = "gini", random_state = 100,max_depth=3, min_samples_leaf=5)
However even with 100,000 records i'm getting very poor result with accuracy around 15-20%. considering how predictable data is(data is generated based on finite set of rules) i was expecting very high accuracy.
I'm i doing something wrong, i want get the high accuracy in classifying data(predicting Result) based on features given, can you suggest some models that might work well this kind of data. what about tensorflow and neural network approach?
data:
https://github.com/sachinhegde6/machinelearningdata
machine-learning scikit-learn pandas machine-learning-model data-science-model
asked 4 mins ago
Sachin HegdeSachin Hegde
1
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Sachin Hegde is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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add a comment |
$begingroup$
I have a well defined data where i have cleaned up my data to final form which has 20 features mapping to a number between 1 to 100. Upto 5 features are enabled(value set to 1) for each row. The data looks something like below
Result|f1|f2|...f19|f20
45 |0 | 1|... 1 | 0
92 |0 | 0|... 1 | 1
I'm trying to build machine learning models that can give me good accuracy and preferably models which can handle warm_start since each iteration generates some data that i need to fit into existing build model.
below are 2 classifiers that i tried to set some baseline
randclf = RandomForestClassifier(n_estimators=50)
decclf = DecisionTreeClassifier(criterion = "gini", random_state = 100,max_depth=3, min_samples_leaf=5)
However even with 100,000 records i'm getting very poor result with accuracy around 15-20%. considering how predictable data is(data is generated based on finite set of rules) i was expecting very high accuracy.
I'm i doing something wrong, i want get the high accuracy in classifying data(predicting Result) based on features given, can you suggest some models that might work well this kind of data. what about tensorflow and neural network approach?
data:
https://github.com/sachinhegde6/machinelearningdata
machine-learning scikit-learn pandas machine-learning-model data-science-model
asked 4 mins ago
Sachin HegdeSachin Hegde
1
New contributor
Sachin Hegde 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 well defined data where i have cleaned up my data to final form which has 20 features mapping to a number between 1 to 100. Upto 5 features are enabled(value set to 1) for each row. The data looks something like below
Result|f1|f2|...f19|f20
45 |0 | 1|... 1 | 0
92 |0 | 0|... 1 | 1
I'm trying to build machine learning models that can give me good accuracy and preferably models which can handle warm_start since each iteration generates some data that i need to fit into existing build model.
below are 2 classifiers that i tried to set some baseline
randclf = RandomForestClassifier(n_estimators=50)
decclf = DecisionTreeClassifier(criterion = "gini", random_state = 100,max_depth=3, min_samples_leaf=5)
However even with 100,000 records i'm getting very poor result with accuracy around 15-20%. considering how predictable data is(data is generated based on finite set of rules) i was expecting very high accuracy.
I'm i doing something wrong, i want get the high accuracy in classifying data(predicting Result) based on features given, can you suggest some models that might work well this kind of data. what about tensorflow and neural network approach?
data:
https://github.com/sachinhegde6/machinelearningdata
machine-learning scikit-learn pandas machine-learning-model data-science-model
asked 4 mins ago
Sachin HegdeSachin Hegde
1
New contributor
Sachin Hegde 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 well defined data where i have cleaned up my data to final form which has 20 features mapping to a number between 1 to 100. Upto 5 features are enabled(value set to 1) for each row. The data looks something like below
Result|f1|f2|...f19|f20
45 |0 | 1|... 1 | 0
92 |0 | 0|... 1 | 1
I'm trying to build machine learning models that can give me good accuracy and preferably models which can handle warm_start since each iteration generates some data that i need to fit into existing build model.
below are 2 classifiers that i tried to set some baseline
randclf = RandomForestClassifier(n_estimators=50)
decclf = DecisionTreeClassifier(criterion = "gini", random_state = 100,max_depth=3, min_samples_leaf=5)
However even with 100,000 records i'm getting very poor result with accuracy around 15-20%. considering how predictable data is(data is generated based on finite set of rules) i was expecting very high accuracy.
I'm i doing something wrong, i want get the high accuracy in classifying data(predicting Result) based on features given, can you suggest some models that might work well this kind of data. what about tensorflow and neural network approach?
data:
https://github.com/sachinhegde6/machinelearningdata
machine-learning scikit-learn pandas machine-learning-model data-science-model
machine-learning scikit-learn pandas machine-learning-model data-science-model
asked 4 mins ago
Sachin HegdeSachin Hegde
1
New contributor
Sachin Hegde is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 4 mins ago
Sachin HegdeSachin Hegde
1
New contributor
Sachin Hegde is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 4 mins ago
Sachin HegdeSachin Hegde
1
New contributor
Sachin Hegde is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 4 mins ago
Sachin HegdeSachin Hegde
1
asked 4 mins ago
Sachin HegdeSachin Hegde
1
1
New contributor
Sachin Hegde is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Sachin Hegde is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Sachin Hegde 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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