Comments (4)
sounds good to me.
from golearn.
will then the base be too big and complicated?
IMO, separating the CV-related into a individual sub-package can be just for cleanness.
from golearn.
InstancesTrainTestSplit() is already in the base package so the other alternative is a refactor where you move it to the CV package... but that would be a very thin package which is why IMO it works fine in base.
from golearn.
To be honest, I'm in favour of moving this out into an evaluation
package or similar, so you can keep plain old k-fold cross validation, stratified k-fold cross validation, repeated random subsampling, plus all the stats functions together.
from golearn.
Related Issues (20)
- IsolationForest panic: 0 ClassAttributes (1 expected) HOT 4
- Arch linux support / installation? HOT 2
- The same order of categorical values for Equals function is necessary or not HOT 1
- Example about how to query the model after being trained using KNN ? HOT 4
- Building the KNN Example as a static linked executable fails
- runtime error:cgo argument has Go pointer to Go pointer HOT 2
- neural: Rename `neural.NeuralFunction` -> `neural.Function` HOT 1
- Bad import, was an upstream dependency deleted? HOT 2
- Question: How to convert class name into single quote?
- Any interest in XGBoost? HOT 7
- Implement tanh activation func HOT 2
- Error in download golearn with 'go get' HOT 3
- KNNClassifier has no field or method optimisedEuclideanPredict HOT 2
- golearn can read the .pickle converted csv file ?
- Support for Apple Metal HOT 2
- KNN Classifier saved and loaded models don't give the same results. HOT 1
- KNN.optimisedEuclideanPredict undefined (type *KNNClassifier has no field or method optimisedEuclideanPredict) HOT 6
- Question: Could we save the model and use it next time for reproduction of result? HOT 6
- there is a crash in dbscan algoritm HOT 8
- Update readme cover image
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from golearn.