Unanswered Questions
1,745 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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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:
...
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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1
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993
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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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CommunityBot
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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
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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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5
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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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How to apply oversampling when doing Leave-One-Group-Out cross validation?
I am working on an imbalanced data for classification and I tried to use SMOTE previously to oversampling the training data. However, this time I think I need to use a leave-on group out (LOGO) cross-...
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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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answers
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Time-efficient parallelization of masks for pre-processing a dataset
I have a large dataset (~10M points) in python and I want to filter it using a large number of different custom masks, as part of calculations to create a new but related dataset. Because the dataset ...
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Low Accuracy from Geospatial Random forest ML modeling problem - Training Exported from qGIS, SCP
I am doing a geospatial assessment integrated with ML modeling. The problem is the very low accuracy percentage, as more training features increases, it gets lower. What could be the solution to such ...
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