<html>
<head>
<meta content="text/html; charset=windows-1252"
http-equiv="Content-Type">
</head>
<body bgcolor="#FFFFFF" text="#000000">
Hi.<br>
Can you provide a self-contained example to reproduce on the
issue-tracker?<br>
Maybe you used warm_start=True but changed something about the
dataset, like going from 125 classes to 128?<br>
<br>
This works:<br>
<br>
from sklearn.neural_network import MLPClassifier<br>
gen_class =
MLPClassifier(hidden_layer_sizes=(200,),max_iter=3000,learning_rate='adaptive',alpha=0.025,warm_start=True)<br>
X_train = np.random.uniform(size=(398, 50))<br>
y_train = np.random.uniform(size=398) > .5<br>
gen_class.fit(X_train, y_train)<br>
<br>
best,<br>
Andy<br>
<br>
<div class="moz-cite-prefix">On 10/07/2016 09:51 AM, Aakash Agarwal
wrote:<br>
</div>
<blockquote
cite="mid:CABVTFDuwGrZnb5FZcE5+OY0oNx084xOTwNgMZ_85m-up2xmpLQ@mail.gmail.com"
type="cite">
<div dir="ltr">Hi Guys,
<div><br>
</div>
<div>I am playing around MLP classifier lately. So i have about
450 inputs to classify. Each input is a vector of array size
50. I am trying to fit the model with 90% as train data. </div>
<div><br>
</div>
<div>Size of training data: (398, 50)</div>
<div>Size of testing data: (45, 50) <br clear="all">
<div><br>
</div>
<div>MLP instantiation:</div>
<div>gen_class =
MLPClassifier(hidden_layer_sizes=(200,),max_iter=3000,learning_rate='adaptive',alpha=0.025,warm_start=True)<br>
</div>
<div><br>
</div>
<div>Batch size is auto so it is taking 200 as batch_size. But
when i am fitting the classifier model, i am getting
following error:</div>
<div><br>
</div>
<div>
<div>Traceback (most recent call last):</div>
<div> File "intent_detection_classifier_selection.py", line
452, in <module></div>
<div>
sk_class.gen_class_fitting(gen_class,corp_lsi_train,train_label)</div>
<div> File "intent_detection_classifier_selection.py", line
77, in gen_class_fitting</div>
<div> gen_class.fit(data,label)</div>
<div> File
"/usr/local/lib/python2.7/dist-packages/sklearn/neural_network/multilayer_perceptron.py",
line 612, in fit</div>
<div> return self._fit(X, y, incremental=False)</div>
<div> File
"/usr/local/lib/python2.7/dist-packages/sklearn/neural_network/multilayer_perceptron.py",
line 372, in _fit</div>
<div> intercept_grads, layer_units, incremental)</div>
<div> File
"/usr/local/lib/python2.7/dist-packages/sklearn/neural_network/multilayer_perceptron.py",
line 509, in _fit_stochastic</div>
<div> coef_grads, intercept_grads)</div>
<div> File
"/usr/local/lib/python2.7/dist-packages/sklearn/neural_network/multilayer_perceptron.py",
line 225, in _backprop</div>
<div> loss = LOSS_FUNCTIONS[self.loss](y,
activations[-1])</div>
<div> File
"/usr/local/lib/python2.7/dist-packages/sklearn/neural_network/_base.py",
line 222, in log_loss</div>
<div> return -np.sum(y_true * np.log(y_prob)) /
y_prob.shape[0]</div>
<div>ValueError: operands could not be broadcast together
with shapes (200,128) (200,125)</div>
</div>
<div><br>
</div>
<div class="gmail_signature">
<div dir="ltr">Thanks,
<div>Aakash</div>
</div>
</div>
</div>
</div>
<br>
<fieldset class="mimeAttachmentHeader"></fieldset>
<br>
<pre wrap="">_______________________________________________
scikit-learn mailing list
<a class="moz-txt-link-abbreviated" href="mailto:scikit-learn@python.org">scikit-learn@python.org</a>
<a class="moz-txt-link-freetext" href="https://mail.python.org/mailman/listinfo/scikit-learn">https://mail.python.org/mailman/listinfo/scikit-learn</a>
</pre>
</blockquote>
<br>
</body>
</html>