Unanswered Questions
12,308 questions with no upvoted or accepted answers
22
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1
answer
3k
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Understanding Timestamps and Batchsize of Keras LSTM considering Hiddenstates and TBPTT
What I'm trying to do
What I am trying to do is predicting the next data-point $x_t$ for each point in the timeseries $[x_0, x_1, x_2,...,x_T]$ in the context of a date-stream in real-time, in theory ...
CommunityBot
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10
votes
1
answer
618
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A clear visualization of a two-way ANOVA
To provide a full yet simple picture of a 3-level, one-way ANOVA, I use the following visualization where variation within each group (the filled circles) and variation between the groups (black ...
CommunityBot
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9
votes
2
answers
367
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Are there any graph embedding algorithms like this already?
I wrote an algorithm for generating node embeddings based on the graph's topology. Most of the explanation is done in the readme file and the examples.
The question is:
Am I reinventing the wheel?
...
CommunityBot
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9
votes
4
answers
3k
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Loss Function for Probability Regression
I am trying to predict a probability with a neural network, but having trouble figuring out which loss function is best. Cross entropy was my first thought, but other resources always talk about it in ...
CommunityBot
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9
votes
0
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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 ...
- 3,598
9
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0
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AdaBoost implementation and tuning for high dimensional feature space in R
I am trying to implement the AdaBoost.M1 algorithm (trees as base-learners) to a data set with a large feature space (~ 20.000 features) and ~ 100 samples in R. ...
- 203
8
votes
1
answer
1k
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Gensim LDA model: return keywords based on relevance (λ - lambda) value
I am using the gensim library for topic modeling, more specifically LDA. I created my corpus, my dictionary, and my LDA model. With the help of the pyLDAvis library I visualized the results. When I ...
CommunityBot
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8
votes
0
answers
132
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Training value neural network AlphaGo style
I have been trying to replicate the results obtained by AlphaGo following their supervise learning protocol. The papers specify that they use a network that has two heads: a value head that predicts ...
8
votes
3
answers
691
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Chi-square as evaluation metrics for nonlinear machine learning regression models
I am using machine learning models to predict an ordinal variable (values: 1,2,3,4, and 5) using 7 different features. I posed this as a regression problem, so the final outputs of a model are ...
CommunityBot
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8
votes
1
answer
252
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How to predict advantage value in deep reinforcement learning
I'm currently working on a collection of reinforcement algorithms: https://github.com/lhk/rl_gym
For deep q-learning, you need to calculate the q-values that should be predicted by your network. There ...
CommunityBot
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8
votes
0
answers
3k
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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 ...
8
votes
1
answer
3k
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Decision Trees - C4.5 vs CART - rule sets
When I read the scikit-learn user manual about Decision Trees, they mentioned that
CART (Classification and Regression Trees) is very similar to C4.5,
but it differs in that it supports numerical ...
CommunityBot
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7
votes
3
answers
4k
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Why is 10000 used as the denominator in Positional Encodings in the Transformer Model?
I was working through the All you need is Attention paper, and while the motivation of positional encodings makes sense and the other stackexchange answers filled me in on the motivations of the ...
CommunityBot
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7
votes
4
answers
4k
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How to perform feature selection on dataset with categorical and numerical features?
I am working on a dataset with 30 columns (29 numerical, 1 non-ordinal categorical). I hot-encoded the categorical feature and reached at 35 columns. To improve training efficiency, I want to perform ...
CommunityBot
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7
votes
1
answer
9k
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How is WordPiece tokenization helpful to effectively deal with rare words problem in NLP?
I have seen that NLP models such as BERT utilize WordPiece for tokenization. In WordPiece, we split the tokens like playing to play and ##ing. It is mentioned that it covers a wider spectrum of Out-Of-...
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