All Questions
Tagged with machine-learning warning-messages
9 questions
1
vote
1
answer
74
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ClassifierMeasurements returns strange errors
I am following the example listed on this page ResNet 50 to train a custom classifier and inspect the outcome with ClassifierMeasurements. My training set has 443 images from more than 30 classes. The ...
6
votes
0
answers
186
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How can I prevent errors with ReplicateLayer[]?
I am trying to build a NetGraph[] that takes input of the form {{0.6},{0.6},...,{0.8},{0.8}} and multiplies the last sequence ...
0
votes
0
answers
66
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Unable to replicate Predict/NeuralNetwork example from Help Pages
I am trying to replicate an example right out of the help manual (ref/method/NeuralNetwork). This example compares the convolutional NN versus a fully-connected NN....
3
votes
0
answers
199
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Bug in the classification optimization algorithm for large data sets
I believe that I encountered a bug in Mathematica 12.
The Classify[] function throws errors when simultaneously:
The training set has significantly above $10^5$ ...
2
votes
0
answers
90
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Confusing errors using predict to map between matrices
I'm messing around with the new features involving machine learning in Mathematica 11, and one easy thing to try is to make a machine learn the matrix exponential function. The first silly idea I had ...
4
votes
1
answer
206
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Value for output of layer is inconsistent (implementing SqueezeUNET from Keras)
I'm attempting to implement this neural network in WL: https://github.com/lhelontra/squeeze-unet/blob/master/squeezeunet.py which is a variant of the SqueezeNet network that does image segmentation.
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11
votes
1
answer
870
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How to use an external GPU to train neural networks in Mathematica?
Taking steps in the uncharted territories of eGPUs, I have installed an NVIDIA GeForce Titan Xp GPU on an eGPU enclosure (Mantiz MZ-02) and have connected it to my laptop (HP Spectre x360 - 15-bl075nr ...
1
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0
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116
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6
votes
1
answer
780
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Sentiment analysis of tweets
I want to use Mathematica for a sentiment analysis on tweet-messages. For that purpose i selected several tweets. Each tweet is interpreted by myself as positive (pos) of negative (neg). For example:
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