how to convert python code to MATLAB?

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Min-seok Kim
Min-seok Kim on 14 Dec 2018
Is there way to convert this python code to matlab code?
it's too hard to me :(
how to convert python to matlab???
this is code what I want to convert.
from sklearn.model_selection import train_test_split
import keras
from keras.models import Sequential
from keras.layers import Dense
import numpy as np
np.random.seed(3)
# number of wine classes
classifications = 3
# load dataset
dataset = np.loadtxt('wine.csv', delimiter=",")
# split dataset into sets for testing and training
X = dataset[:,1:14]
Y = dataset[:,0:1]
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.66, random_state=5)
# convert output values to one-hot
y_train = keras.utils.to_categorical(y_train-1, classifications)
y_test = keras.utils.to_categorical(y_test-1, classifications)
# creating model
model = Sequential()
model.add(Dense(10, input_dim=13, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(6, activation='relu'))
model.add(Dense(6, activation='relu'))
model.add(Dense(4, activation='relu'))
model.add(Dense(2, activation='relu'))
model.add(Dense(classifications, activation='softmax'))
# compile and fit model
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=['accuracy'])
model.fit(x_train, y_train, batch_size=15, epochs=2500, validation_data=(x_test, y_test))
please!
  1 Comment
GT
GT on 17 Dec 2018
To the best of my knowledge there is no "automatic" python to MATLAB converter. There are a couple of things you can do:
Hope that this helps

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Answers (2)

Abderrahmane  Bakhouche
Abderrahmane Bakhouche on 20 Feb 2022
# Metamodel regression
X_train, X_test, y_train, y_test = \
train_test_split(LDB1.iloc[:,:-1], LDB1["d"], test_size=0.4, random_state=42)
clf = make_pipeline(SplineTransformer(),
MLPRegressor(alpha=0.0001, hidden_layer_sizes = (20, 10), max_iter = 500000,
activation = 'relu', verbose = 'True', learning_rate_init=0.01))
a = clf.fit(X_train, y_train)
y_pred = clf.predict(X_test)
plt.figure()
# plt.scatter(X_train[P])
plt.scatter(X_test["P"], y_test.tolist(), label="Test values")
plt.scatter(X_test["P"], y_pred, label="Predicted values") # plot network output
plt.title("P vs d (Predicted and test values")
plt.legend()

David Willingham
David Willingham on 30 Sep 2020
Edited: David Willingham on 27 Apr 2021
For Deep Learning there are a few ways to import and export networks into MATLAB.
MATLAB has a direct Tensorflow Importer you could use to import the network:
https://www.mathworks.com/help/deeplearning/ref/importtensorflownetwork.html
For other frameworks, you can import and export via ONNX:
Regards,
Deep Learning Product Manager, MathWorks

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