I am new in Keras and would want to apply a neural network on this dataset: https://www.drivendata.org/competitions/57/nepal-earthquake/
I have proprocessed the dataset transforming categorical variables into numerical with pd.get_dummies pandas method. Also, target (that is 1, 2 or 3 - depending on the damage grade) is tranformed into three columns indicating the probability of being one of those values.
The NN I wrote is simple, but I don't understand what are the values that predict method returns.
# first neural network with keras tutorial from numpy import loadtxt from keras.models import Sequential from keras.layers import Dense import tensorflow as tf import keras.backend as K # define the keras model model = Sequential() # 12 8 3 Accuracy: 57.08 # 25 12 3 Accuracy: 56.89 model.add(Dense(25, input_dim=68, activation='relu')) model.add(Dense(12, activation='relu')) model.add(Dense(3, activation='softmax')) # compile the keras model model.compile(loss='binary_crossentropy', optimizer='adam', metrics=[get_f1]) # fit the keras model on the dataset model.fit(X, y, epochs=5, batch_size=10) predicted = model.predict(test)
This is the output for the first individual:
array([0.09522187, 0.57914054, 0.32563758], dtype=float32)
PD: If you request some additional information or code, please let me know :)
Thanks a lot!!!