Unanswered Questions
3,868 questions with no upvoted or accepted answers
14
votes
0
answers
700
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Convolutional neural network for multi-variate time series?
I want to use CNN architectures for classification of multivariate time-series, where we apply one label to each sequence.
I searched the net for the available designs in the literature and i found ...
- 439
13
votes
0
answers
272
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Logistic regression for classification: are there any analytical solutions for the out-of-sample accuracy?
I run a binary logistic regression, with a binary dependent variable and a continuous independent one.
Now I want to evaluate the out-of-sample performance of the classification algorithm so obtained. ...
- 2,578
12
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0
answers
2k
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Computing a bootstrap confidence interval for the prediction error with the percentile and the BCa method
I have two related questions regarding the computation of a non-parametric bootstrap confidence interval for the prediction error.
Setting: I have a sample S from a data population P and a learner L, ...
CommunityBot
- 1
10
votes
2
answers
2k
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Random Forest: Class specific feature importance
I'm using the bigrf R-package to analyse a dataset with ca. 50.000 observations x 120 variables, classified into two groups.
After growing a forest of 1000 trees, ...
CommunityBot
- 1
9
votes
1
answer
179
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Is there a ML or DL tool that can learn to detect periodically occurring patterns in a one dimensional time series?
I am trying to create a tool that labels refrigerator temperature readings. A reading is taken every 5 minutes, and its label identifies whether of not it was taken while the refrigerator was ...
- 10k
8
votes
1
answer
809
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How to predict routes using clustering data
I've been working on a ship route prediction algorithm such that given the past and current trajectory of a ship I am able to estimate the future one. The trajectories are represented as a sequence of ...
CommunityBot
- 1
8
votes
0
answers
209
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When is there a free lunch?
The no free lunch theorem (NFL) states that
Theorem (Wolpert and Macready 1997) Let $A$ be any learning algorithm for the task of binary classification with respect to the
$0−1$ loss over a ...
- 3,086
8
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0
answers
2k
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What is the intuition for testing seasonal difference with OCSB test and its correct application?
I have daily time series data of a shop's revenue. Now I would like to test for seasonal differencing with the OCSB test originally intrduced in (Osborn et al. (1988): Seasonality and the Order of ...
- 103
8
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0
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14k
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True positive, false negative, true negative, false positive definitions for multiclass-multilabel classification?
I'm trying to apply some evaluation metrics to several clustering methods. I thought that I knew them basing on the multiclass confusion matrix, considering the rows as the actual classes and the ...
8
votes
1
answer
8k
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Micro vs weighted F1 score
In a multi-label or multi-class classification setting, when choosing between a micro or a weighted F1 score, what shall I take into account?
The main upside of choosing macro is that one gets a ...
CommunityBot
- 1
8
votes
1
answer
832
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How to subset alternatives in nested multinomial logistic regression?
I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...
CommunityBot
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7
votes
0
answers
349
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Features for binary time-series event prediction
This question is somewhat inspired by the answer to Features for time series classification.
The difference to that question is that I have a dataset with multi-dimensional time-series where I have ...
- 561
7
votes
0
answers
183
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How to combine noisy and noise-free datasets to train a model
Overview
Suppose I have two datasets, both of which consist of rows of features and their matching labels. One of these datasets is noise-free and its labels correspond to the ground truth, but the ...
- 3,407
7
votes
1
answer
870
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Multi-label classification: Predict product category
I want to predict to which product category a product belongs. A total of 400k products need to be translated from the old (less refined) to the new product category tree. (E.g. alarm clock used to ...
CommunityBot
- 1
7
votes
0
answers
259
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why use diagonal $\Sigma$ when working with Bayes decision theory?
My prof. said in the class that for Bayes decision rule, the likelihood is Gaussian and in practice, we will almost always work with a diagonal $\Sigma$. Why is that? I know that a diagonal $\Sigma$ ...
- 94.9k