Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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10 views

Lego minifigure facial recognition: where to start?

I'm interested in starting a project that will identify the face of a Lego minifigure from a digital photo. I eventually want to do a "face swap," but I'd like to start with the challenge of ...
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29 views

How is clustering used in the unsupervised training of a neural network?

How is clustering used in the unsupervised training of a neural network? Can you provide an example?
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58 views

In which cases is the categorical cross-entropy better than the mean squared error?

In my code, I usually use the mean squared error (MSE), but the TensorFlow tutorials always use the categorical cross-entropy (CCE). Is the CCE loss function better than MSE? Or is it better only in ...
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Can Bert be used to extract embedding for large categorical features?

I've lot of training data points (i.e in millions) and I've around few features but the issue with that is all the features are categorical data with 1 million+ categories in each. So, I couldn't use ...
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22 views

How can I train a Deep Learning model using degraded photos and their clean version to correct photos

I have 5000 degraded pictures ( pixelated, blurry, too much luminosity ... ) and their clean versions, and I would like to train a model so that it can predict how to correct future pictures. I've ...
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18 views

How do I save an Ensemble Learning model?

I need to save it to my PC so that I can run it with a simple .load() function if something disconnects on the platform I'm using (Google Colab). For demonstration purposes, I just want to load the ...
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A problem about the relation between 1-oracle and 2-oracle PAC model

This problem is about two-oracle variant of the PAC model. Assume that positive and negative examples are now drawn from two separate distributions $\mathcal{D}_{+}$ and $\mathcal{D}_{-} .$ For an ...
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27 views

How can we prove this inequality, related to the generalization error, without using the Rademacher complexity?

This is an inequality on page 36 of the book Foundations of Machine Learning, but the author only states it without proof. $$ \mathbb{P}\left[\left|R(h)-\widehat{R}_{S}(h)\right|>\epsilon\right] \...
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Convert a PAC-learning algorithm into another one which requires no knowledge of the parameter

This is part of the exercise 2.13 in the book Foundations of Machine Learning (page 28). You can refer to chapter 2 for the notations. Consider a family of concept classes $\left\{\mathcal{C}_{s}\...
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19 views

How does the weight update formula for logistic regression work?

I am trying to use Logistic Regression to make a spam filter, but I am having trouble understanding the weight update part. I have processed my email dataset, and I have an attribute vector of the top ...
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Is there any paper that uses truncated neural networks?

Recently, I've found good success in truncated neural networks ie functions of the form $$ g=f1_{[-M,M]^d}, $$ where $f:\mathbb{R}^d\to\mathbb{R}^n$ is a feed-forward neural network and $1_{[-M,M]^d}$ ...
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Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?

I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs). The basic idea that I am wanting to get into involves separating crops from weeds ...
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Why are traditional ML models still used over deep neural networks?

I'm still on my first steps in the Data Science field. I played with some DL frameworks, like TensorFlow (pure) and Keras (on top) before, and know a little bit of some "classic machine learning" ...
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25 views

How can I match numbers with expressions?

Let's say I have the number 123.45 and the expression one hundred twenty-three and forty-five cents. Can I develop AI to identify these two values as a match? If I can, how should I do that?
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42 views

Suggestion for finding the stable regions in spiral galaxy data?

I am working with a data set that consists of the actual pitch angle (given as PA(Y)) and the pitch angle at each radii (listed from 1 to 217). In the image below, ...
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438 views

What is the formula for the momentum and Adam optimisers?

In the gradient descent algorithm, the formula to update the weight $w$, which has $g$ as the partial gradient of the loss function with respect to it, is: $$w\ -= r \times g$$ where $r$ is the ...
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48 views

Why isn't there a model playing FPS like CoD or Battlefield already existing?

Assuming we had an unlimited time to train a model and a very powerful machine to use our model in real-time (hello quantum computer), I'd like to know why no one could achieve to build an AI able to ...
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66 views

Why is the average reward plot for my reinforcement learning agent different than the usual plots?

I'm building an RL agent using SARSA and Q-Learning for testing its capabilities. The environment is a 10x10 grid, where it gets a reward of 1 if he reaches the goal while he takes -1 every time he ...
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29 views

How to Layer based Feature extraction?

I have read that in deep networks you can engineer each layer for a particular purpose with regards to feature learning. I'm wondering how that is actually done and how it is trained? In addition ...
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55 views

Is there a mathematical formula that describes the learning curve in neural networks?

In training a neural network, you often see the curve showing how fast the neural network is getting better. It usually grows very fast then slows down to almost horizontal. Is there a mathematical ...
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25 views

pooling m datasets in MICE imputation

I'm trying to understand MICE imputation process, I have read some articles and I have understood how the imputation happens, but I didn't get the pooling step. After analyzing the resulting datasets ...
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2answers
56 views

Does summing up word vectors destroy their meaning?

For example, I have a paragraph which I want to classify in a binary manner. But because the inputs have to have a fixed length, I need to ensure that every paragraph is represented by a uniform ...
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1answer
32 views

Given enough graphical data, could you train an AI to plot a polynomial graph based on the input conditions?

Good day everyone. I am curious if it is possible for an AI to plot a time-series graph based on a single input. Using free fall impact as an example. Assuming we drop a ball from height 100m and ...
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Rarely predict minority class imbalanced datasets

I have a dataset in which class A has 99.8%, class B 0.1% and class C 0.1%. If I train my model on this dataset, it predicts always class A. If I do oversampling, it predicts the classes evenly. I ...
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46 views

Why machine learning instead of simple sorting and grouping?

I have a hard time formulating this question(I'm not knowledgeable enough I think), so I'll give an example first and then the question: You have a table of data, let's say the occupancy of a ...
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2answers
48 views

Is there any classifier that works best in general for NLP based projects?

I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a ...
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Is it acceptable to use various training sets for the individual models when using a majority vote classifier?

So I am trying to use a majority vote classifier combining different models and I was wondering if it is acceptable to use different training sets for the individual models (including different ...
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1answer
53 views

Interpretation of feature selection based on the model

The description of feature selection based on a random forest uses trees without pruning. Do I need to use tree pruning? The thing is, if I don't cut the trees, the forest will retrain. Below in the ...
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1answer
51 views

How to use AI for language recognition?

Given an audio track, I'm trying to find a way to recognize the audio language. Only within a small set (e.g. English vs Spanish). Is there a simple solution to detect the language in a speech?
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158 views

Why can neural networks generalize at all?

Neural networks are incredibly good at learning functions. We know by the universal approximation theorem that, theoretically, they can take the form of almost any function - and in practice, they ...
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1answer
76 views

What is the $\ell_{2, 1}$ norm?

I'm reading this paper and it says: In this paper, we present a multi-class embedded feature selection method called as sparse optimal scoring with adjustment (SOSA), which is capable of addressing ...
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52 views

Are PAC learning and VC dimension relevant to machine learning in practice?

Are PAC learning and VC dimension relevant to machine learning in practice? If yes, what is their practical value? To my understanding, there are two hits against these theories. The first is that ...
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19 views

Reasoning behind $Zero$ validation accuracy in the following ResNet50 model for classification

I have written this code to classify Cats and dogs using Resnet50. Actually while studying I came to the conclusion that Transfer learning gives very good accuracy for deep learning models, but I ...
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FastAi How to turn off crop in ImageDataBunch

I just trained my birds model. It works fine when I was testing it with close pictures. But when I moved the pictures further away my camera, the model was not able to detect birds. My guess is in ...
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1answer
37 views

How to describe an keras Model in a scientific report

how would you describe a machine learning model in a scientific report? It should be detailed but I just listed the hyperparameters... Have you got more important properties?
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1answer
38 views

How to make DNN learn multiplication/division?

A single neuron with 2 weights and identity activation can learn addition/subtraction as the 2 weights will converge to 1 and 1 (addition), or 1 and -1 (subtraction). However, for multiplication and ...
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Find the nearest object in a image which is captured from camera?

Objective : To find the nearest object (closer distance object) in the single camera image. But Image Contains multiple objects shown below: I searched in the net and found this formula to ...
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62 views

Why information gain with entropy as impurity function can't be used as a splitting method for Decision Tree Regression?

In Decision Tree Regression, we can use 'Reduction in Variance' or MSE (Mean Squared Errors) as splitting methods. There are methods like Gini Index, Information Gain, Chi-Square for splitting on ...
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Flattened vector observation or convolutional neural network input?

This is more of a general question of how to model/preprocess 'visual' state-observations to an Agent in Reinforcement Learning that I'll illustrate with an example. Say you have a reinforcement ...
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Reinforcement learning possible with big action space?

I’m experimenting with reinforcement learning for a 2D pixel plotting task, and am running into an issue that (I think) has to do with the big action space. It goes like this: The Agent gets two ...
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1answer
61 views

What is the difference between linear and non-linear regression?

In machine learning, I understand that linear regression assumes that parameters or weights in equation should be linear. For Example: $$y = w_1x_1 + w_2x_2$$ is a linear equation where $x_1$ and $...
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What is the input for the prior model of VQ-VAE?

I'm trying to implement the VQ-VAE model. In there, a continuous variable $x$ is encoded in an array $z$ of discrete latent variables $z_i$ that are mapped each to an embedding vector $e_i$. These ...
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1answer
40 views

Why does the denoising autoencoder always returns the same output?

I am trying to implement a denoising autoencoder (DAE) to remove noise from 1024-point FFT spectra. I am using two types of spectra: (1) that contain a distinctive high amplitude spectral peak and (2) ...
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1answer
57 views

Are neurons in layer $l$ only affected by neurons in the previous layer?

Are artificial neurons in layer $l$ only affected by those in layer $l-1$ (providing inputs) or are they also affected by neurons in layer $l$ (and maybe by neurons in other layers)?
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How would an AI learn the concept of the words “repeat twice”?

In a hypothetical conversation: Person A - "Repeat the word 'cat' twice". Person B - "cat cat". I'm thinking about how a human or AI can learn the concept of "...
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1answer
42 views

Finding the optimal combination of inputs which return maximal output

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
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1answer
88 views

Which AI methods are most appropriate for login face recognition?

I want to make a face authentication application. I need to approve the face during the login based on whether the registered face and the login face match. Which are the possible appropriate AI ...
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26 views

Train a competitive layer on nonnormalized vectors using LVQ technique

How can we train a competitive layer on non-normalized vectors using LVQ technique ? an example is given below from Neural Network Design (2nd Edition) book The net input expression for LVQ networks ...
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2answers
98 views

Can a neural network be used to predict a sequence of integers based on dataset of previously produced random numbers?

What i really want to do, is to predict an integer sequence of (5 numbers with values from 1 to 50) for example based on a big dataset of other 5 numbers sequences with same values range created by ...
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27 views

How can I predict the nutrients in dishes given the ingredients used to prepare them?

I want to know which algorithm will work most efficiently for calculating nutrients present in a food dish if I am giving the ingredients used in the food. Basically, let us assume that I want to make ...