Unanswered Questions
3,349 questions with no upvoted or accepted answers
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Python : Feature Matching + Homography to find Multiple Objects
I'm trying to use OpenCV via Python to find multiple objects in a train image and match it with the key points detected from a query image. For my case, I'm trying to detect the tennis courts in the ...
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Using the Python Keras multi_gpu_model with LSTM / GRU to predict Timeseries data
I'm having an issue with python keras LSTM / GRU layers with multi_gpu_model for machine learning.
When I use a single GPU, the predictions work correctly ...
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Unable to transform (greatly performing) Autoencoder into Variational Autoencoder
Following the procedure described in this SO question, I am trying to transform my (greatly performing) convolutional Autoencoder into a Variational version of the same Autoencoder. As explained in ...
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Tensorflow v1 Dataset API AttributeError with ndim
I'd like to make pipeline for optimizing Gpu and Cpu.
Dataset
It's about 10000 datapoint and 4 description variables for the regression problem.
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Fine tuning accuracy lower than Raw Transfer Learning Accuracy
I've used transfer learning on Inception V3 with ImageNet weights on Keras with Tensorflow backend on python 2.7 to create an image classifier. I first extracted and saved the bottleneck features from ...
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6
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Keras - Implementation of custom loss function with multiple outputs
I am trying to replicate (a way smaller version) the AlphaGo Zero system. However, in the network model, I am having a problem. The loss function I am supposed to implement is the following:
$$l = (z -...
CommunityBot
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How to deal with missing data for Bernoulli Naive Bayes?
I am dealing with a dataset of categorical data that looks like this:
...
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Gridsearch XGBoost for ensemble. Do I include first-level prediction matrix of base learners in train set?
I'm not quite sure how I should go about tuning xgboost before I use it as a meta-learner in ensemble learning.
Should I include the prediction matrix (ie. df containing columns of prediction results ...
CommunityBot
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What is the minimum number of times a word needs to appear in word2vec training corpus for quality results?
When training a word2vec model with, eg, gensim, you can specify the minimum times a word needs to be seen (with the parameter min_count). The default value for this seems to be 5.
Are there any ...
CommunityBot
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Maths of Xavier initialization
The paper I read is Glorot et al (2010). And the math part is in Section 4.2.1.
Formula (5) and (10) make sense to me but I cannot derive formula (6) and (7) myself from (2) and (3).
I found many ...
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Connect output node to next hidden node in RNN
I'm trying to build a neural network with an unconventional architecture and a having trouble figuring out how. Usually we have connections like so, where $X=$ input, $H=$ hidden layer, $Y=$ output ...
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What preprocessing steps to be followed before image comparison?
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For example I am trying to find the similarity between two images using skimage - SSIM. The code block will be as follows
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Tuning Gradient Boosted Classifier's hyperparametrs and balancing it
I am not sure if it is a correct stack. Maybe I should have put my question into crossvalidated.
Nevertheless, I perform following steps to tune the hyperparameters for a gradient boosting model:
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how to propagate error from convolutional layer to previous layer？
I've been trying to implement a simple convolutional neural network. But I've been stuck at this problem for over a week.
To be specific, assume there are 3 layers in a convolutional pass, marked as ...
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Triangle Pattern Recognition on Financial Market with Python
I'm working on a personal project to find Triangles on any stock in Python.
I detect the max and min points (shift(-5,+5) because if I consider only shift(-1+1) I have a lot of lines) and write lines ...
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