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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7 views

Why does my NN produce Nan values after something like the 3rd iteration?

After about the 2nd or 3rd iteration/epoch, the outputs from my forward prop all contain NaN values. The softmax function produces extreme values which probably is the reason for this. However, I am ...
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12 views

Is federated learning a privacy breach?

Is federated learning a privacy breach, given that the model transmission, for a period of time, may cause the adversarial to reach and manipulate the model and the data?
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1answer
28 views

How Machine Learning Studies Correlation?

This is my problem: I have 10 variables that I intend to evaluate two by two (in pairs). I want to know which variables have the strongest relationships with each other. And I'm only interested in ...
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27 views

What is the difference between random and sequential sampling from the reply memory?

I was working on an RL problem and I am confused at one specific point. We use replay memory so that the network learns about previous actions and how these actions lead to a success or a failure. ...
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11 views

Tensorflow and Keras model having same parameters, hyperparameters, weight and bias initialization give different accuracy?

I have made sure that layers,parameters, hyperparameters,kernel_initialization, bias_initialization, seed and dataset are all equal. But still the output for both the models are different. ...
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22 views

What is the best option to test the data set of images using weka? [migrated]

I have two hundred and fifty images, and extracted the features from them and put them in an Excel file, how to use the weka program so that the first 200 images for training and the remaining fifty ...
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28 views

Show that if $H$ is PAC learnable (in the standard one-oracle model), then $H$ is also learnable in the two-oracle model

Consider a variant of the PAC model in which there are two example oracles: one that generates positive examples and one that generates negative examples, both according to the underlying distribution ...
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15 views

How to implement AdamW? [on hold]

I have implemented AdamW but I am not getting good results, is there some mistake in my implementation? ...
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1answer
15 views

Real time ticket similarity

I'm dealing with a "ticket similarity task". Every time new tickets arrive at the help desk (customer service), I need to compare them and find out about similar ones. In this way, once the operator ...
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1answer
36 views

Why does estimation error increase with $|H|$ and decrease with $m$ in PAC learning?

Why does estimation error increase with $|H|$ and decrease with $m$ in PAC learning? I came across this statement in the section 5.2 of the book "understanding machine learning: from theory to ...
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7 views

Learning to rank on collections of ordered objects?

Are there examples of LTR algorithms applied to variable length lists of ordered objects? E.g. perhaps 4 specific photos in a sequence layout would rate higher than another 3 or another 4 where the ...
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16 views

Threshold selection for Siamese network hyper-parameter tuning

I'm interested in modeling a Siamese network for facial verification. I've already written a simple working model that inputs feature vectors generated from two CNNs with shared weights then outputs a ...
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1answer
22 views

Image classification with an associated matrix

I have a dataset of images with 9 different classes. However, there are different categories with the same type of associated image and only can be differentiated with an associated matrix in my ...
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2answers
35 views

How to express accuracy of a regression ANN that uses MSE loss function?

I have a regression MLP network with all input values between 0 and 1, and am using MSE for the loss function. The minimum MSE over the validation sample set comes to 0.019. So how to express the '...
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39 views

Can ML be used to curve fit data based on dataset of example fits?

Say I have x,y data connected by a function with some additional parameters (a,b,c): $$ y = f(x ; a, b, c) $$ Now given a set of data points (x and y) I want to determine a,b,c. If I know the model ...
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27 views

why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output

HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ? and will this lead ...
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16 views

Which AI algorithm is great for mapping between two XML files

My work colleague got a project with a lot of work that is not hard or complicated. The problem is simple but it is a lot of work. We have two XML files with a lot of variables in it. Not only is ...
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1answer
31 views

Reinforcement learning with hints or reference model

In Reinforcement Learning, when I train a model, it comes up with its own set of solutions. For example, if I am training a robot to walk, it will come up with its own walking gait, such as this Deep ...
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1answer
35 views

How many hidden layers are needed for this training data set

I'm trying to separate classes in 3D space, the data are as in the sketch below: There are 3 classes: 0,1,2; and with the look into the sketch, it seems that I need 3 planes to separate the classes, ...
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10 views

Is there any reason to believe a ml pipeline that works on dataset A will work on dataset B where both have similar meta features?

I’m working on generating an automl pipeline(a combination of data cleaning and transformation algorithms applied to a dataset then generate a model) that works on a new dataset by looking for past ...
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1answer
23 views

Is it compulsary to normalize the dataset if doing so can negatively impact a Binary Logistic regression performance?

I am using raw data set with 4 feature variables (Total Cholesterol, Systolic Blood Pressure, Diastolic Blood Pressure, and Cigraeette count) to do a Binominal Classification (find stroke likelihood) ...
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19 views

How to build naive bayes graph from data

For an university assignment I have to use the HuginLite software to do some probabilistic inferences with different algorithms. One of these algorithms is Naive Bayes but its graph is not built ...
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15 views

Applying ML algorithms to data-sets with similar meta-features?

Is there any grounds for assuming an algorithms applied to a data-set that created a decently accurate model will perform as well on a different data-set with meta-features chosen and evaluated by ...
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1answer
43 views

Should the biases be zero or randomly initialised?

I'm initialising DNN of shape [2 inputs, 2 hiddens, 1 output] with these weights and biases: ...
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2answers
153 views

Should I use the Threadripper 2920X or Ryzen 7 3700X?

Update 2 The OS I'm using is Windows 10, since we have WSL, I also use Ubuntu to run the code. The code is written in Python. I know there are thousands of factors which affect the final performance ...
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28 views

Implementing JSON with facial recognition software [closed]

I wrote the code for my facial recognition using Python, open-CV and it works, but I wanted to go further. Therefore, I created a JSON file that contains details about the people in my image dataset. ...
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23 views

How to update Loss Function parameter after compilation

I used following custom loss function. ...
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2answers
182 views

How would an AI learn idiomatic phrases in a natural language?

After an AI goes through the process described in How would an AI learn language?, an AI knows the grammar of a language through the process of grammar induction. They can speak the language, but they ...
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1answer
28 views

What does an oscillating validation error curve represent?

I have been training my CNN for a bit now and, while both the training loss and the training error curves are going down during training, both my validation loss and my validations error curves are ...
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0answers
34 views

When to use RMSE as opposed to MSE and vice versa?

I understand that RMSE is just the square root of MSE. Generally, as far as I have seen, people seem to use MSE as a loss function and RMSE for evaluation purposes, since it exactly gives you the ...
2
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2answers
85 views

How can I determine the mathematical relation between the input and output variables?

I would like to take in some input values for $n$ variables, say $R$, $B$, and $G$. Let $Y$ denote the response variable of these $n$ inputs (in this example, we have $3$ inputs). Other than these, I ...
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2answers
25 views

How does one create a non-classifying CNN in order to gain information from images?

How do I program a neural network such that, when an image is inputted, the output is a numerical value that is not the probability of the image being a certain class? In other words, a CNN that doesn'...
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0answers
24 views

How to implement fisherface algorithm and how much time will it take?

I found on the web that fisherface is the best algorithm for face detection. Before investing deeply into it, I just want to know how hard is it to implement it and how much time will it take. I am ...
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1answer
13 views

How can I cluster based on the complementary categories?

K-means tries to find centroid and then clusters around the centroids. But what if we want to cluster based on the complement? For example, suppose we have a group of animals and we want to cluster ...
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1answer
38 views

Understanding the intuition behind Content Loss (Neural Style Transfer)

I'm trying to understand the intuition behind how the Content Loss is calculated in a Neural Style Transfer. I'm reading from an articles: https://medium.com/mlreview/making-ai-art-with-style-transfer-...
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2answers
131 views

What does the symbol $\mathbb E$ mean in these equations?

I came across some papers that use $\mathbb E$ in equations, in particular, this paper: https://arxiv.org/pdf/1511.06581.pdf. Here is some equations from the paper that uses it: $Q^\pi \left(s,a \...
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1answer
114 views

Can a neural net learn to read?

I am a student of last year of computer engineering and lately I have been very interested in AI. Fields such as ML and DL seem very disruptive to me. A few months ago I saw an interview of Bill ...
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1answer
39 views

How is transfer learning used to mitigate catastrophic forgetting in neural networks?

How can transfer learning be used to mitigate catastrophic forgetting. Could someone elaborate on this?
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1answer
57 views

What is the difference between classical and quantum machine learning?

By classical, I mean the current Machine learning Algorithms we have, according to the current status of Machine Learning field, some we have or might have not gained the in-depth aspects which will/...
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3answers
53 views

What should we do when we have equal observations with different labels?

Suppose we have a labeled data set with columns $A$, $B$, and $C$ and a binary outcome variable $X$. Suppose we have rows as follows: ...
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39 views

Implementation of SVM - theory to practice

I'm studying Support Vector Machines in the machine learning course, I'm a computer scientist, I've quite understood how SVM are designed thanks also to 16. Learning: Support Vector Machines - MIT. ...
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0answers
30 views

Is it possible to control asymptotic behaviour of neural network models?

Is it possible to specify what the asymptotic behaviour of a Neural Networks (NN) model should be? I am thinking on NN which try to learn a mapping $\vec y=f(\vec x)$ with $\vec x$ a vector of ...
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1answer
17 views

Create optimizer object using the tf.keras.optimizers.get function

I am trying to have the type of optimizer as a variable in the hyperparameter tuning phase. For that reason I am trying to use the tf.keras.optimizer.get function ...
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1answer
19 views

Train on big dataset (1mil + images)

I am in the process of collecting a huge dataset of Human poses captured images to create a model to classify poses. My question is how will I be able to train on this massive dataset? I have ...
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15 views

Suggestions for Deep Learning for regression on huge 3D volumes

I have a dataset of 3D images (volumes) with dimensions 400x250x400. For each input image I have an output of the same dimensions. I would like to train a machine learning (or deep learning) model on ...
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0answers
7 views

How to use machine learning to create combine of opposite images side by side

Inspired by: Two Worlds Pictures I just want to create a Machine Learning Model that can automatically combine the opposite images into 1 image. I am thinking about 2 possible solutions: Pose ...
2
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1answer
45 views

Using ML to analyze Facebook posts

First of all, I should mention that I have a very basic knowledge of ML so I apologize if this question seems trivial or stupid. I am working on a small personal project, basically an app that ...
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8 views

Mobile App Recommendation: How to get the rate of a specific user submit for a specific application

I have a mobile app recommendation project, so I need data set which has user-app matrix-rate. Actually, I want to know what rate does a specific user submit for a specific application. in other words,...
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1answer
75 views

How to develop neural networks for face recognition?

I have developed face recognition algorithms by using pre-built libraries in Python and open CV. However, suppose if i want to make my own neural network algorithm for face recognition, what are the ...
4
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1answer
71 views

An intuitive explanation of Adagrad, its purpose and its formula

It (Adagrad) adapts the learning rate to the parameters, performing smaller updates (i.e. low learning rates) for parameters associated with frequently occurring features, and larger updates (i.e. ...