Great package! Thank you for creating this. I was testing out the MLPClassifier() model with this package--see the complete code below--and was getting an AttributeError: 'list' object has no attribute 'ndim' when I used the package as is. I added some code below to convert the model coefficient elements into numpy arrays and it seemed to work. Am I missing something? Was this an error with the package or was it an error in how I was using the package? Either way, thank you again. Note: I was using Python 3.7.4.
import numpy as np
import sklearn_json as skljson
from sklearn.neural_network import MLPClassifier
from sklearn import datasets
# Load data
df = datasets.load_iris()
X = df.data
y = df.target
# Instantiate and fit model
model_fit = MLPClassifier(solver='lbfgs', alpha=1e-5,
hidden_layer_sizes=(15,), random_state=1).fit(X, y)
file_name = "model.json"
# Convert model to json
skljson.to_json(model_fit, file_name)
# Convert json back to model
deserialized_model = skljson.from_json(file_name)
## THE MISSING PIECE: THE LISTS INSIDE COEFS_ NEED
## TO BE CONVERTED TO ARRAYS
for i, x in enumerate(deserialized_model.coefs_):
deserialized_model.coefs_[i] = np.array(x)
# This prediction should run if the code really works
deserialized_model.predict(X)
Great package! Thank you for creating this. I was testing out the MLPClassifier() model with this package--see the complete code below--and was getting an
AttributeError: 'list' object has no attribute 'ndim'when I used the package as is. I added some code below to convert the model coefficient elements into numpy arrays and it seemed to work. Am I missing something? Was this an error with the package or was it an error in how I was using the package? Either way, thank you again. Note: I was using Python 3.7.4.