Closed NehKulkarni closed 6 years ago
Here's how I do it, on the MNIST data set. Expose the weights and interaction matrix via w,V = model.weights
. You can just insert this cell into the notebook example.ipynb
.
model = TFFMClassifier(
order=2,
rank=10,
optimizer=tf.train.AdamOptimizer(learning_rate=0.001),
n_epochs=50,
batch_size=1024,
init_std=0.001,
reg=0.01,
input_type='dense',
seed=42
)
model.fit(X_tr, y_tr, show_progress=True)
predictions = model.predict(X_te)
# visualize weights
w,V = model.weights
plt.imshow(w.reshape(28,28));
plt.title('Weight (Linear Term)');
for idx,col in enumerate(V.T):
plt.figure();
plt.imshow(col.reshape(28,28))
plt.title('Interaction Feature {}'.format(idx))
model.destroy()
Hi, Is it possible to display all the interaction factors between the variables?