Unanswered Questions

9,107 questions with no upvoted or accepted answers
15
votes
0answers
249 views

Formal proof of vanilla policy gradient convergence

So I stumbled upon this question, where the author asks for a proof of vanilla policy gradient procedures. The answer provided points to some literature, but the formal proof is nowhere to be included....
12
votes
0answers
1k views

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 ...
10
votes
1answer
786 views

Input for LSTM for financial time series directional prediction

I'm working on using an LSTM to predict the direction of the market for the next day. My question concerns the input for the LSTM. My data is a financial time series $x_1 \ldots x_t$ where each $x_i$...
10
votes
0answers
360 views

ngram and RNN prediction rate wrt word index

I tried to plot the rate of correct predictions (for the top 1 shortlist) with relation to the word's position in sentence : I was expecting to see a plateau sooner on the ngram setup since it ...
8
votes
2answers
82 views

Model for Differing Number of Rows per Observation

Looking to build a response model (click or no click) on marketing data which displays varying number of offers to a person. I don't want to model which offer they click but do they click any of the ...
8
votes
2answers
111 views

how to generate automatically images meshing up different shapes with a deep learning software?

My pursuit is to generate something like a grottesque(a kind of painting producing human-animals and plants hybrids). I need to do something like this painting in order to create an art exhibition. I ...
7
votes
2answers
1k views

Forecasting Multiple (few hundreds) uni-variate time series with inflated zeros

Hello Practitioners, Being a newbie seeking help to gain experience in Data Science. Lets take a scenario where a big company wants to forecast its sales (a specific product) across different stores ...
7
votes
1answer
344 views

A/B testing: How to calculate p-value on post test segments?

My question on A/B testing is about doing post test segmentation analysis. For example: I run an A/B test on my website to track bounce rate. On the treatment group, i put a video to explain ...
7
votes
0answers
1k views

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. ...
6
votes
0answers
116 views

ground truth fit is worse than cross validated fit on noisy data?

I am having these weird results when playing around with cross validation that I would greatly appreciate to have any comments. Briefly, I have a lower mean squared error (MSE) when doing regression (...
6
votes
0answers
135 views

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? ...
6
votes
0answers
95 views

bias and variance trade off related question

I am having difficulty to understand the expected squared errors formula in this website: $y=f(x)+e$ true regression line $\hat{y}=\hat{f}(x)$ your estimated regression line $error(x)=\bigg(\...
6
votes
2answers
1k views

Loss Function for Probability Regression

I'm 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 ...
6
votes
0answers
1k views

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 ...
6
votes
1answer
297 views

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 ...

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