Questions tagged [representation]

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Using categorical and continuous variables in Deep Learning

I want to apply a MLP to some business seller data. I found that the data is a mix of both categorical and continuous features. For what I read it is not advisable to feed a neural network with both ...
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1answer
28 views

Good chromosome representation in a VRPTW genetic algorithm

I have a genetic algorithm for a vehicle routing problem with time windows and I need to implement certain modifications. I am not sure what would be the best chromosome representations. I have tasks ...
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21 views

What observations can you perceive from the following table?

I am preparing my thesis presentation and I want to give a clear understanding of the data that I have collected for the jury members. I understood the data very well, but I feel like I am lacking a ...
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1answer
33 views

Clustering with categorical as well as numerical features

I have dataset consisting of house prices for example. The dataset contains features such as: house size, monthly rent, house colour, location, year the house was built. I wanted to group these all ...
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25 views

Representation sample size- n [closed]

Need help with identifying a representation sample size 'n'. Let's say I have a very large population- infinite number of participants. I am picking the random sample from this infinite population. I ...
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41 views

Autoencoder works but VAE does not - KL divergence loss drops to zero

I have an image encoding problem, to which I have successfully applied an autoencoder. But when I try to convert this into a VAE framework by introducing KL divergence loss and sampling from a unit ...
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0answers
18 views

Can the input and output be different in a variational autoencoder?

While the autoencoder and the variational autoencoder typically decode back to the same input space that was passed in, I am working on a more generic encoder-decoder structure, where the output is a ...
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1answer
39 views

What does it exactly mean when we say that PCA and LDA are linear methods of learning data representation?

I have been reading on representation learning and I have come across this idea that PCA and LDA are linear methods of data representation, however, auto-encoders provide a non-linear way. Does this ...
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1answer
25 views

A way to init sentence embedding for unsupervised text clustering, better than glove wordvec?

For unsupervised text clustering, the key thing is the init embedding for text. If we want to use deepcluster for text, the problem for text is how to get the init embedding from deep model. BERT can ...
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2answers
24 views

Is it possible to compress a sequence of numbers through an autoencoder?

Specifically: I would like compress a set of coordinates, which map to the locations of 1's in a binary image, and then decode back to the original set. For instance, for a 16x16 image, the input ...
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1answer
76 views

Embedding of list of objects

I have a dataset where each sample is a list of ordered items, lets say grocery list , and a label from 6 categories . each list can have up to 120 items but the mean items is 12 items in a list. i ...
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1answer
16 views

What are the sparse and dense vector ? I cant undestand ,can you explain to me?please.Why do we use for?

I am new to neural networks, embeddings, etc. I am struggling understanding things like sparse representation, embeddings, and especially sparse vectors. Could you explain these to me? Why do we need ...
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1answer
24 views

Representing user information

I have a task of representing a users feature matrix , i have features like gender , age etc but I also have a multivalue feature called as "movies watched" which is essentially another table of ...
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11 views

Standard(s) for data representing measurement times with their interval of validity?

Is there a standard for representing the time interval of a measurement? Any actual measurement is made at a point in time with, perhaps, an interval over which it is considered valid. For example, ...
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2answers
23 views

Difference between n-dimensional of length m and m-dimensional of length n?

With respect to classifying the MNIST digits I've seen the input representation referred to as both a one-dimensional array of 748 elements and a 784-dimensional vector. Are these perspectives always ...
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1answer
94 views

PCA, why variance of eigen values is measure of its utility?

Source - Murphy, 12.3 Heuristic for assessing applicability of PCA. Let the empirical covariance matrix Σ have eigenvalues λ1≥λ2≥···≥λd>0, with mean λ. Explain why the variance of the eigen values, ...
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134 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? ...
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1answer
14 views

Membership ratio graph

Does anyone know how the what the kind of graph in this image is called? Each color represents a class and the height of the color, in a particular instant, represents the ratio of elements that ...
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2answers
44 views

Is there any option to represent 160 discrete variables each one with their own color in scatter plot?

Good morning, I want to know if it is possible to represent with different colors in scatter plot more than 10 parameters instead of putting others and assign a color if the amount of parameters ...
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1answer
299 views

What does 'Linear regularities among words' mean?

Context: In the paper "Efficient Estimation of Word Representations in Vector Space" by T. Mikolov et al., the authors make use of the phrase: 'Linear regularities among words'. What does that mean ...
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0answers
18 views

Daily-level variables and weekly-level variables at the same model

I am running a model which has NPS (Net Promoter Score) as its target and various predictors among which some CSAT (Customer Satisfaction) data. The rest of the predictors are good to use at daily ...
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1answer
241 views

Why ELMo's word embedding can represent the word better than glove?

I have read the code of ELMo. Based on my understanding, ELMo first init an word embedding matrix A for all the word and then add LSTM ...
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1answer
87 views

How to deal with Optional Input

I'm from the vision world and only worked with pixels from 0-255, ignoring any side effects. My current problem is different, in the way that I cannot rely on the input data. What my problem is: I ...
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1answer
529 views

faster alternatives to sparse.model.matrix?

I have a large dataset that is entirely categorical. I'm trying to train with it using xgboost, so I must first convert this categorical data to numerical. So far I've been using sparse.model.matrix() ...
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1answer
63 views

Learning Football Player Stats like FIFA's by only the game result [closed]

It is a general question on how to learning representation of one entity but the dataset is mixed with a lot of other entities, which their statis are always waiting to be learnt. The question is ...
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1answer
444 views

Neural Nets: unordered sets of ordered tuples as features of data

I'm working on a very small scale pet project in which inputs are essentially sets of (x, y) pairs, and are to be classified into categories, using deep learning, specifically using Keras (I know this ...
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1answer
378 views

How to learn from multiple data sources with different input variables but the same underlying pattern?

I will explain with an example: Let's say you have 2 factories that produce pulp paper. Each have similar processes where the laws of physics give the same outcome. Now let's say this 2 factories ...
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2answers
11k views

Why don't tree ensembles require one-hot-encoding?

I know that models such as random forest and boosted trees don't require one-hot encoding for predictor levels, but I don't really get why. If the tree is making a split in the feature space, then isn'...