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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Prerequisites for Artificial Intelligence and Machine Learning?

I am a beginner in the field of AI and ML. Before jumping into or learning something I have the habit of researching prior condition that has to be needed in my learning process and also I have to get ...
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41 views

Search vs planning in artificial intelligence

I'm studying artificial intelligence following the Russell & Norvig book. We did a search and planning part that for me is the same (at least on the representation). I'd like to know what is the ...
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How does the Random Forest classification function

I was going the through Random forest classification trying to understand it and I stumbled on two equation and I was wondering if anyone knows their name. what are the names of the theorms or ...
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24 views

Introduction to computer science for ML [closed]

I have learned python syntax (from books like fluent python or python cookbook etc.) and I want to learn the underlying concepts of computer science (in an abtract way), do you have some books/courses ...
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16 views

Dimension Reduction - Which feature should remove to reduce the dimension of the matrix

Let's suppose that we have the following 2 tables: If we want to reduce the dimension by one(in every table) which feature we should remove and why ? I am confused about the way that i should work ...
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Is it possible to compute a whole convolution layer at once?

I have an input of 32×32×3 and I want to feed it to a convolution layer that output 32×32×16 feature maps. I know that I can compute a single feature map as matrix multiplication. But my question is, ...
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Cross Entropy Function

I've seen two versions of the cross entropy cost function, and conflicting information about it. \begin{equation}J(\theta) = -\frac{1}{N} \sum_{n=1}^N\sum_{i=1}^C y_{ni}\log \hat{y}_{n_i} (\theta)\end{...
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Simple Question About the Nature of Supervised Learning Predictive Models in Relation to their Training Data

Would a deployed or deployment-ready (i.e., already-trained) supervised learning model have a 100% accuracy rate for predictions on the training data (if you were to run the training data through it ...
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Is there any intersection in the applications of multi-agent reinforcement learning and more traditional branches of machine learning?

From my limited understanding, it seems like the structure of problems that multi agent reinforcement learning attempts to attack is quite different from the structure of problems in more traditional ...
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Linear regression: not noramalising by y's norm

I was recently reading an article on Pearson correlation, and OLS coefficients. I came across the following section. Finally, these are all related to the coefficient in a one-variable linear ...
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42 views

What is the best algorithm known to learn the regular expression from a set of positive examples?

I have a blackbox program that generates a set of strings. What is the best regular expression learner that I can use to learn (approximate) what the blackbox program uses as a generator? Note that I ...
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maximum tensor rank for computer vision tasks

Most computer vision tasks do not require 4+ ranked tensors. Are there any use cases for tensors with ranks more than 4 in computer vision? Are there any use cases for deep learning in general?
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Prior probability in HMM

This is the HMM model considered in the question And this is the emission probabilities for the respective states. There are two emission values, bringing an umbrella and not bringing an umbrella. ...
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how can i find that the size of tree which is built by C5.0 algorithm is good?

I built C5.0 for balancing data with 16 attributes. and the size of my model is 125 and it used 15 attributes for building model.how can i find the size is good?
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Question about implementing GAN(Generative Adversial network)?

so most examples I've seen create two NN-s, train them, then they stack them, make the discriminator part untrainable and then train this stacked NN, why do we do this? So loss, that is calculated on ...
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27 views

Data points as outcomes of a random experiment

It is well known that Random variable is a function from sample space of a random experiment to $\mathbb{R}$. Consider the following sentences from deep learning book Let $\{x^{(1)}, \cdots , x^{...
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Why is Agnostic PAC learnability a stronger criterion as compared to the PAC learnability?

I am trying to understand the mentioned question. According to me, it should be other way around as it is easier to find hypothesis which is approximately correct compared to the optimal hypothesis in ...
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33 views

What is the most efficient way to test whether a set $X \subset \{0, 1\}^n$ and its complement $\{0, 1\}^n \setminus X$ are linearly separable?

I am interested in algorithms that have optimal running time, and ideally which are also very easy to implement. If you can also give some tips on how to implement the algorithm(s) you mention in the ...
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72 views

Which time series prediction techniques are useful given harmonic properties?

I have a time series dataset where events have harmonic properties, and seemingly the nature of the event's early segments can determine the remainder of the event (see example 1's oscillations). ...
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26 views

Weighting function for Non Uniform Learning

Consider a hypothesis class $H = \cup_{n=1}^{\infty} H_n$, where for every $n\in N$, $H_n$ is finite. Find a weighting function $w : H ->[0, 1]$ such that $\sum_{h \in H} w(h) ≤ 1$ and so that for ...
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21 views

How to compute the derivative using chain rule of hidden layer (more than 5 neurons for hidden layer) with bias

In the given problem having 8 inputs with 5 hidden layers and 3 output layers and bias(b1) on hidden layers and bias(b2) on ...
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26 views

Sorting using AI / neural net

I have a search operation taking place on a server that essentially queries images using OpenCV against other images from a database. Since each image query ...
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1answer
30 views

Is SGD used in machine learning libraries?

SGD (Stochastic Gradient Descent) is used in most libraries of different programming languages. Is it also used in machine learning libraries?
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How to understand a equation related to speaker recognition?

This question refers to the following paper: Support Vector Machines for Speaker and Language Recognition, W. M. Campbell, J. P. Campbell, D. A. Reynolds, E. Singer, P. A. Torres-Carrasquillo, ...
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31 views

How to make sure matrix completion can generate a matrix with values in expected range?

I am doing a matrix completion project. Assume that I have an incomplete matrix like ...
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68 views

How to find the best exploration parameter in a Monte Carlo tree search?

I've developed a Monte Carlo tree search algorithm in checkers. Here is my question. What should be the value of $C$, the exploration parameter in the following formula described in Monte Carlo Tree ...
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Interactions between predictive analytics, ML, and case-based and rules-based reasoning

For my studies on economy, I work on prediction of judicial decisions. I don't really understand the interactions between several concepts: predictive analytics machine learning case-based reasoning ...
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40 views

How can we get small test error reducing only train error?

My question is about mathematical part of machine learning algorithms, especially about using it in neural networks. We train network reducing train error and I was thinking about how then test error ...
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50 views

feature selection in decision tree classifier [closed]

i want to build decision tree classifier, and i have no idea how to extract feature from text (my file is text) can anyone help me? is BOW, N-gram orTF-IDF useful?
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28 views

How to calculate information gain in ID3?

I am trying to implement a decision tree classifier using ID3 algorithm. According to Aritificial Intelligence - A Modern Approach, information gain of attribute A ...
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50 views

Is it possible to achieve greater than perfect compression using machine learning and big data?

Imagine Google wanted to make their chrome browser faster. Let "database" be all the machines which serve content from Google's servers, including Search and Google cloud services. Google begins using ...
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Loss function for spurious data

I am trying to train an autoencoding neural network (autoencoder) to reconstruct seismograms. Previous studies employing this technique (e.g. Valentine & Trampert, 2012) used an L2 (mean squared ...
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How is momentum an approximation of Hessian based optimization?

In the answer to "what is the Hessian" at this site: https://stackoverflow.com/questions/23297090/how-calculating-hessian-works-for-neural-network-learning the person answering the question ...
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56 views

Random Forest - Conditional Permutation Importance

I've been looking for the most unbiased algorithm to find out the feature importances in random forests if there are correlations among the input features. Besides the most commonly preferred ...
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Help with understanding why we need an expectation in the loss

I am reading the paper SV2P - Stochastic Varaiational Video Prediction (https://arxiv.org/abs/1710.11252). In it the authors use the loss shown in the image: Why do we need expectation in the ...
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What do we mean by “spectral domain” in the context of graphs?

What do we mean by the spectral domain in the context of graphs? For example, I have heard that graph convolutions are easiest to define in the spectral domain. When it comes to the word "spectral", I ...
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34 views

Algorithm suggestion for ticket routing system using Machine Learning

Background info I'm a beginner in ML, let me start there. I'm trying to implement an intelligent system that can route a ticket (in a ticketing system), to the appropriate place based on a few ...
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162 views

Condensed Nearest Neighbor Explanation

I have a question regarding the Condensed Nearest Neighbor algorithm from ...
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How to go about designing a quiz that changes difficulty based on user performance?

I thought about using a machine learning algorithm to learn the performance patterns of the quiz taker and model the next quiz based on how he/she performed. So each question will have a difficulty ...
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Are fully connected layers required for convnets?

I have a reinforcement learning model I'm trying to create for a grid based game. One of the features of the game is that the game board can get bigger mid game, although I know this is a problem that ...
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1answer
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k-means clustered data: how to label newly incoming data

I have a data set with labels that were produced by a $k$-means clustering algorithm. Now there is some data (with the same data structure) from another source and I wonder what is the most sensible ...
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point clouds in machine learning

What is the purpose of point clouds in machine learning? Consider the following suggestion: Say I have a table (per year) of records (such as days) each of which is made of n real numbers such as ...
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how does bagof features work in MATLAB? [closed]

I tried to use machine learnign in matlab using bagoffeatures to captures features and teach the code betwee two types of plots. However, bagofFeatures could not detect ant features. this is my plot: ...
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33 views

Is there any Boosting algorithm with closed-form solutions?

My goal is to formulate the learning and generalization phases of any Boosting algorithm as a matrix-vector operation. Through Google, I found a good pdf (*) describing several boosting algorithms ...
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PCA collision - finding matrix with different numbers that reduced with PCA to same numbers

I want to find matrix X 2*2: a1 b1 a2 b2 a1!=a2 b1!=b2 so that after im applying PCA on that with number of prinicpal compoments 1 i wish to get matrix 2*1: c c i want to find collision
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35 views

What does “Temporal extent” mean?

I am reading Long-term Temporal Convolutions for Action Recognition and under the Section 3.1, I read this: To investigate the impact of long-term temporal convolutions, we here study network ...
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25 views

How do we fix area of detectors in object detection?

I have gone through various articles on medium and also some from other sites trying to understand SSD. I am able to figure out most of the things from articles except this one. They always say that ...
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Is the preprocessing process using the tfidf vectorizer really useful for model learning?

I am a student who is studying machine running alone. As far as I know, the Tf-idf Vectorizer is a function that combines the Count Vectorizer and the Tf-idf Transformer. I was wondering if the Tf-idf ...
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Is it still transfer learning if you consider input as well as output? (neural networks)

I'm new to the CS stack exchange, so a fond hello to you all! I joined since I have a question I've been curious about. I have recently been running some experiments in transfer learning - ...
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446 views

Single Layer Perceptron vs Multi Layer Perceptron

Why the single layer perceptron has a linear activation function while the Multi Layer Perceptron has a non-linear activation function ? What is the potential of the Multi Layer Perceptron respect of ...