Questions tagged [machine-learning]

Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.

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21 views

ML - What are the benefits of transforming variables with long tail?

What are the obvious benefits of transforming variables with long tail distributions? To extend it more, why the machine learning algorithms will perform better afer such a transformation?
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17 views

Math behind Multi-class linear discriminate analysis (LDA)

I have a question about Linear Discriminant Analysis (LDA) for the purpose of Dimensionality Reduction. So I understand for the algorithm to calculate for $k$ projection vector(s) you need to ...
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44 views

Modified sign function VC dimenson

If we have $f:\mathbb{R} \rightarrow \{\pm 1\}$, and $\mathcal{F}$ and $\mathcal{F}'$, what are the VC dimensions of $\mathcal{F} = \{sign(\prod_{i=1}^n (x-\theta_i), \forall a_i \in \mathbb{R} \}$ $\...
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18 views

How to choose better performance based on margins from two kernels

In SVM, how can or cannot the margin attained by two different kernels on a single dataset be used to determine which classifier has better performance on the dataset? Can we just plot the decision ...
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1answer
99 views

Classes of circle rims

The input space is a unit circle, $\mathcal{X} = \mathbb{S}^1 \subset \mathbb{R}^2$. There is class $\mathcal{F}$ of arcs on $\mathbb{S}^1$, where a point is labeled 1 if it is on the arc, and 0 ...
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35 views

How can a classifier using Laplacian kernel achieve no error on the input samples?

If we have a sample dataset $S = \{(x_1, y_i),\dots,(x_n,y_n)\}$ where $y_i = \{0,1\}$, how can we tune $\sigma$ such that there is no error on $S$ from a classifier using the Laplacian kernel? ...
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1answer
69 views

VC dimension of only the rim of a unit disk

Suppose we have an origin centered circle, ie $x^2 + y^2 =1$, so it's in $\mathbb{R}^2$ (2D). It will be classified as 1 if it lies only on this arc, and will be labeled 0 otherwise. What is the VC ...
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34 views

How to find clusters of a set of points in n-dimensional space that are furthest from unwanted points

I have a list of 25 points and their coordinates in a 512-dimensional space. I have 8 target points and 17 points I need to avoid (the 17 points to avoid also have differences in priority of how ...
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50 views

Labeled points in $\{0,1\}^n$ such that every linear separator requires exponential weights

I want to find labeled samples in $\{0,1\}^n$ such that the Perceptron algorithm takes $2^{\Omega(n)}$ steps to converge. One way to do this would be to find a sequence of labeled examples that are ...
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199 views

How do you calculate the training error and validation error of a linear regression model?

I have a linear regression model that I've implemented using Gradient Descent and my cost function is a Sum of Squares Error function. I've split my full dataset into three datasets, a training set, a ...
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20 views

Stochastic Gradient Descent for Multi-Class SVM

I'm trying to compute the optimization problem for a multi-class SVM loss function with $L2$ regularization. $\displaystyle f(W) = \frac{1}{n}\sum_{i=1}^n\sum_{c\neq y_i} \max\{0,1-w_{y_i}^Tx_i+w_c^...
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14 views

Algorithm Sequence classification(anomaly detection)

I have a problem statement where i am having many inputs lets say A,B,C,D.... and this inputs can take any real value(e.g A-a1,a2,a3, B-b1,b2). Now, i have file which will be have record of the all ...
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How can one algorithmically define the required amount of centroids in K-Means clustering?

Say I have a dataset of n vectors. These are, by nature, clustered so that there is a significant distance difference between any two points within a cluster and any two points in separate clusters. ...
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2answers
84 views

How can Machine Learning be used to find attributes/characteristics of graphs?

I am aware ML is not necessary for many graph classification problems (as the graph theorists have many clever solutions), but I'm specifically interested in ML approaches to these types of questions. ...
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11 views

FOIL system for learning PROLOG rules from facts

I'm trying to use FOIL, a system from the 1990s developed by Ross Quinlan, to learn Prolog rules from facts. However, the input file syntax is tricky for me. Could someone provide me an example input ...
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1answer
24 views

Uniform Convergence and VC Theroy

I've started reading more about statistical learning theory, specifically this paper right here and I cannot understand the following part: It turns out the conditions required to render empirical ...
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16 views

Why do we need to change the (weight decay) regularization parameter when changing the number of inputs that neural network is being trained with?

I am currently working my way through Michael Nielsen's ebook Neural Networks and Deep Learning and I am reading about overfitting and (L2) regularization. In this subsection, the process of L2 (a.k.a ...
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21 views

How to get synonyms from definitions using Bayes algorithm

I work on a project: an online dictionary where the user can find definitions of a word he's looking for. My supervisor asked us to add synonyms using machine learning. He recommend us to use Bayes ...
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24 views

Simple back propagation example

Sorry if this is too simplistic of a question, but over the last couple of months I have been working through the course mathematical foundations of machine learning at my college. I think I am really ...
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37 views

Backprop formula question

I'm reading this chapter https://www.deeplearningbook.org/contents/mlp.html of the Deep Learning book, and on page 209, they have this equation (assume there is no regularizer and no bias parameter): $...
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1answer
38 views

Proof of uniform convergence if VC dimension is finite

In the book »Understanding Machine Learning: From Theory to Algorithms«, written by Ben-David and Shalev-Shwartz, there is a proof which I do not understand. The context is proving that if a ...
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1answer
23 views

Learning a specific functional form with machine learning

Suppose I have only three independent features (x, y, z) as the input to some machine learning routine (e.g. neural network). From some domain knowledge, I know ...
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20 views

proof that SimpLe is fully expresive

Refering to this paper "SimplE Embedding for Link Prediction in Knowledge Graphs" by Seyed Mehran Kazemi and David Poole in 2018 : In page 4, about the proof of SimpLE being fully expressive, I ...
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14 views

Equation to find the collaboration between neighbors in SOM in unsupervised learning

In Kohonen's SOM algorithm, the equation to find the collaboration is: $$ \mathit{Damp}(i,j) = \exp\left(-\frac{\mathit{LDist}(i,j)^2}{2\sigma^2}\right) $$ I know that LDist is the lattice distance ...
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30 views

training SimpLE model for link prediction on knowledge graph

Referring to this paper by Prof Kazemi, Prof Poole on SimpLE model for link prediction on knowledge graph. In page 3, the paragraph on learning SimpLE Models, I understand that we have a batch of ...
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2answers
30 views

Time efficient way to implement Multi-Armed-Bandits?

I'm doing a research on Multi-Armed Bandit (MAB) problem with approx. 1 million arms. In contrast, the number of iterations is of course much larger, about 10-20 million. Most MAB-algorithms require ...
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1answer
39 views

Is Artificial intelligence simply taking decisions on the basis of values produced by a machine learning model

I am researching on AI and its working. Whenever I try to search for AI algorithms, ML algorithms come up. Then, I read the differences between ML & AI. One of the key points mentioned was "AI is ...
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49 views

how many parameters do we need to estimate for a general probabilistic model

Its a question from a test in machine learning. I have 3 binary variables x1,x2 and x3 (which means that each one of them can be either 1 or 0), each one of them has a binary output y (can be 0 or 1). ...
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26 views

Artificial Neuron: question on definition and inhibited signals

This is an artificial neuron of a NOT function from Rojas's ML book. I have a question on it's behavior. It's my understanding that the neuron produces a signal if it's inputs $x_1$ summed are $\geq ...
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1answer
68 views

Approximating Deep Neural Networks (DNNs) with Binarized Neural Networks (BNNs)

I am working currently as a research intern on Binarized Neural Networks where the weights and the activations of the network are binary. The architecture of this type of networks makes them memory ...
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50 views

Calculate probability in graphical model

I have the following graphical model, in which I wish to compute $p(Intelligence = 1|Letter = 1, SAT = 1)$ But I'm not sure how to rewrite $p(Intelligence = 1|Letter = 1, SAT = 1)$? I was told to ...
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34 views

How machine learning libraries are created?

I would like to know how machine learning libraries (or in general libraries at large scale) are created. I mean Python doesn't have inbuilt array system but c has. So how they are supported for ...
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23 views

Is it possible to create an age estimation by face program using deeplearning with my laptop?

My computer specs: Processor type Intel(R) Core(TM) i7-8550U CPU @1.80GHz 1.99GHz Installed RAM 8.00 GB System Type 64 bit operating system i also have Intel UHD graphics 620. I am starting an ...
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2answers
102 views

Being stuck and frustrated with my masters project

I'm doing a masters in CS that requires me to implement from scratch most of the neural network models and because python libraries aren't applicable to what i want. The problem is that i don't feel ...
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17 views

Clustering customer with string data

I'm looking for a customer clustering solution. I have done a lot of research on the machine learning level to find algorithms that could fit my needs but I can't find much information when the data ...
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1answer
97 views

Asymptotic analysis for machine learning algorithms

I wanted to know if it would practical and useful to analyse machine learning algorithms in terms of asymptotic computational complexity. I have noticed this is very uncommon. However, I believe it ...
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17 views

Weights vs Training ML

The weights of Machine Learning models are learned during the training process. Why is said that the higher values of weights leads to the overfitting of the model? Why is it necessary to have low ...
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1answer
54 views

Energy consumption off CNN models

I want to calculate/estimate the energy consumption for the different convolutional neural networks. Is there any possibility to measure the energy consumed by AlexNet for example with a tool or with ...
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26 views

Why does my EM algorithm not converge?

Any ideas why my likelihood probability for this EM algorithm doesn't converge (have slope of 0) to "find" the three clusters? I've tried increasing the iterations, which makes the slope nearly ...
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19 views

Which machine learning should I choose for a one->list relation

I'm trying to write machine learning software that will predict a list of 3 values from a given number input (reverse grayscale). There is a function determining values of the list to the grayscale, ...
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1answer
160 views

Measures of performance in machine learning

I'm new to machine learning and struggle to interpret the results I get from different measures of performance. If for several prediction models I have e.g. accuracy, precision, recall, F1, FPR, and ...
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53 views

What kind of bigram probability smoothing is this?

I hope it isn't off topic but I need to understand this example. Given the corpus 12 1 13 12 15 234 2526 and smoothing factor of ...
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1answer
29 views

Confused on Variational AutoEncoder

I'm a bit confused on how Variational Autoencoders are trained. In particular I'm confused on how the latent variable is generated for each input. My questions are as follows: When running ...
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14 views

Relationship between keystroke pattern and emotion

There are API provided by Google and Microsoft that takes as input the image of a person and output a probability distribution of the person's mood. I'm wondering if there an API that can take as ...
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18 views

What is the main concept of using lexical,linguistic, semantic or syntactic approach in NLP for cyberbullying

Am really in need of some explanation, am working on a nlp cyberbullying detection tool which i will deploy to the web using django framework, however, am stuck on some idea, can someone explain to me....
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1answer
25 views

Using a point as an input for a perceptron

Can a point be used as the input for a perceptron/neural net? The relationship between the two numbers that make up a 2D point does not affect the output, but does this not matter when the ...
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42 views

Can anyone think of applications of a 3 way (k-way) dot product in computer science or data mining

I have developed a locality sensitive hashing algorithm for the 3-way or k-way dot product. When I say 3-way dot product I mean the following. Suppose we have $x,y,z \in [-1,1]^{S}$ for $S \in \...
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24 views

Image classification with zero data

Given an image of a biology diagram, I would like to classify the diagram into these 4 categories: Plant Animal Cell Anatomy However, I don't have any training data. I would like to avoid the ...
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1answer
31 views

Mapping categorical data in K-nearest neighbour

I have a data set which contains categorical data, for example: ...
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1answer
40 views

Text detection in computer vision

I'm curious about the way text recognition works in machine learning(or more generally, the question of object vs not object) in computer vision. How are systems trained when the not-object data set ...

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