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1500 questions
24
votes
3 answers

How to add a new category to a deep learning model?

Say I have done transfer learning on a pre-trained network to recognize 10 objects. How can I add a $11^{th}$ item that the network can classify without losing all the 10 categories I already trained and the information from the original pre-trained…
nnrales
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3 answers

Keyword/phrase extraction from Text using Deep Learning libraries

Perhaps this is too broad, but I am looking for references on how to use deep learning in a text summarization task. I have already implemented text summarization using standard word-frequency approaches and sentence-ranking, but I'd like to explore…
shanky_thebearer
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23
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3 answers

Nearest neighbors search for very high dimensional data

I have a big sparse matrix of users and items they like (in the order of 1M users and 100K items, with a very low level of sparsity). I'm exploring ways in which I could perform kNN search on it. Given the size of my dataset and some initial tests I…
cjauvin
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23
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2 answers

Why do activation functions have to be monotonic?

I am currently preparing for an exam on neural networks. In several protocols from former exams I read that the activation functions of neurons (in multilayer perceptrons) have to be monotonic. I understand that activation functions should be…
Martin Thoma
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23
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14 answers

Data Science conferences?

This is a similar question like the Statistics Conferences question at CrossValidated What are the most significant annual Data Science conferences? Rules: Include a link to the conference Please include links for the talks (be it youtube, the…
Dawny33
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23
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4 answers

How to perform one hot encoding on multiple categorical columns

I am trying to perform one-hot encoding on some categorical columns. From the tutorial I am following, I am supposed to do LabelEncoding before One hot encoding. I have successfully performed the labelencoding as shown below #categorical…
radioactive
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23
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4 answers

Incremental Learning with sklearn: warm_start, partial_fit(), fit()

I have built an ML model with the goal of making predictions for targets of the following week. In general, new data will come in and be processed at the end of each week and be in the same data structure as before. In other words, the same number…
Adam
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23
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4 answers

In SVM Algorithm, why vector w is orthogonal to the separating hyperplane?

I am a beginner on Machine Learning. In SVM, the separating hyperplane is defined as $y = w^T x + b$. Why we say vector $w$ orthogonal to the separating hyperplane?
Chong Zheng
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23
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4 answers

Dimensionality and Manifold

A commonly heard sentence in unsupervised Machine learning is High dimensional inputs typically live on or near a low dimensional manifold What is a dimension? What is a manifold? What is the difference? Can you give an example to describe…
alvas
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23
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2 answers

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. Looking at Sutton,Barto- Reinforcement…
Markus Peschl
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23
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8 answers

Rationale behind most published works in medical imaging trying to reduce false positives

In medical image processing, most of the published works try to reduce false positive rate (FPR) while in reality, false negatives are more dangerous than false positives. What is the rationale behind it?
Hunar
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23
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4 answers

What statistical model should I use to analyze the likelihood that a single event influenced longitudinal data

I am trying to find a formula, method, or model to use to analyze the likelihood that a specific event influenced some longitudinal data. I am having difficultly figuring out what to search for on Google. Here is an example scenario: Image you own a…
Peter Kirby
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23
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4 answers

Is logistic regression actually a regression algorithm?

The usual definition of regression (as far as I am aware) is predicting a continuous output variable from a given set of input variables. Logistic regression is a binary classification algorithm, so it produces a categorical output. Is it really a…
joews
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23
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1 answer

How does Gradient Descent and Backpropagation work together?

Please forgive me as I am new to this. I have attached a diagram trying to model my understanding of neural network and Back-propagation? From videos on Coursera and resources online I formed the following understanding of how neural network…
Mohamed Mahyoub
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23
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3 answers

How to grow a list of related words based on initial keywords?

I recently saw a cool feature that was once available in Google Sheets: you start by writing a few related keywords in consecutive cells, say: "blue", "green", "yellow", and it automatically generates similar keywords (in this case, other colors).…
nassimhddd
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