Unanswered Questions
2,127 questions with no upvoted or accepted answers
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Why is my Keras model not learning image segmentation?
Edit: as is turns out, not even the model's initial creator could successfully fine-tune it. This is most likely a problem of implementation, or possibly related to the non-intuitive way in which the ...
CommunityBot
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9
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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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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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3
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What Clustering Method Should I Use?
My data is a group of 10 thousand points (each having an node location (x,y)) that are spread across a plane. They are also chromatically-colored based on their weight.
I need to finalize a bayesian ...
CommunityBot
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6
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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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6
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1
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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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6
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2
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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:
...
CommunityBot
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6
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2
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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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6
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0
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614
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Adversarial Learning for Semantic Segmentation
I am incorporating Adversarial Training for Semantic Segmentation from Adversarial Learning for Semi-Supervised Semantic Segmentation.
The idea is like this:
The discriminator takes as input a ...
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6
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1
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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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6
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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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6
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2
answers
4k
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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 ...
CommunityBot
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Model misclassifies digits from MNIST dataset after trained it on Digits dataset
I am training a machine learning model to classify digits in order to detect and solve a Sudoku puzzle. Here’s the approach I followed:
This is the pipeline I am following:
Classifier training: I ...
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2
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Multidimensional scaling producing different results for different seeds
I took the data from here and wanted to play around with multidimensional scaling with this data. The data looks like this:
In particular, I want to plot the cities in a 2D space, and see how much it ...
CommunityBot
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