Prem George
Prem George
We can generate plot for two columns like  Is it possible to show the plot for clusters of full data, something like in kohonen NN, but just like the...
Is there any fix for this ``` ERROR: neupy 0.8.2 has requirement tensorflow=1.10.1, but you'll have tensorflow 1.14.0 which is incompatible. ``` Thanks
Hi, I am running algorithms.SOFM(n_inputs=79, n_outputs=2, learning_radius=1, step=0.1, shuffle_data=True, weight='sample_from_data',verbose=True) data array size is 4.3gb running windows 10 machine with 32GB RAM, Set to 200 epoch, each epoch taking 25mins,...
@KevinLiao159 May I know how to make_recommendation out of this model ``` predictions = GMF_model.predict([df_test.userId.values, df_test.movieId.values]) ``` Thanks
Hi, I am using scorecardpy for long time now, now I did a comparison of model metrics between two types of normalization Norm1: Normalising all Features using scorecardpy Vs Norm2:...
I am applying LIME explanations for the autokeras model In the documentation it says  Is it possible to return classes from the autokeras model? This is just to make...
I'm converting autoKeras model to onnx, getting a issue in the onnx model, the prediction result of python model and onnx model are different, onnx team suggesting The category mapper...
Hi, 1. Is it possible to set verbose = 0 2. disable directory for storing the search outputs, when I run in docker it's an issue to manage folder, if...
Keras Sequential model returns classes from ``` model.classes_ ``` and history from ``` model.history.history['accuracy'] model.history.history['val_accuracy'] model.history.history['loss'] model.history.history['val_loss'] ``` After export, is it possible to get these two ``` ExportedautoKeras_model =...
Hi, I am trying to convert autokeras model to onnx, i get error ``` from autokeras import StructuredDataClassifier model = StructuredDataClassifier(max_trials=100) model.fit(x=X_train, y=y_train, validation_data=(X_valid, y_valid), epochs=1000, verbose=1) autoKeras_model = model.export_model()...