# Questions tagged [machine-learning]

Theoretical questions about Machine learning, especially Computational Learning Theory, including Algorithmic Learning Theory, PAC learning, and Bayesian Inference

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### Why is Bayesian filtering better than Neural Networks when classifying spam?

According to several people on StackOverflow Bayesian filtering is better than Neural Networks for detecting spam. According to the literature I've read that shouldn't be the case. Please explain!
801 views

### Linear Genetic Programming

I have a few questions about linear genetic programming. I'm struggling to find much information on them, hopefully someone here can help me, it would be much appreciated. 1) Initialisation: When ...
277 views

### Fuzzy K-modes clustering how to find the cluster centers

I'm trying to understand [fuzzy k-modes] algorithm (look mainly at page 3) in order to implement it. I'm stuck at the calculation of cluster centers they said as shown in the link https://...
94 views

### Designing an appropriate training set for CART classification using imbalanced data

I'm experimenting with using CART (or maybe Random Forest) to classify genomic data. There are essentially two classes, whereof one is the 'normal' state and the other is the 'exceptional' state. Now,...
176 views

### what is the equivalence class of a given polytree representing a directed graphical model?

Let $T$ be a binary tree, where the internal nodes are $Y_1,...,Y_n$ and the leafs are $X_1,...,X_m$. (The $Y$s and the $X$s will eventuall represent a random variable in a Bayesian network.) We can ...
209 views

### K-means with centres outside the data?

Say we want to split a cube in $\mathbb{R}^{64}$ into 10 pieces. NN, nearest-neighbor or Voronoi splits, take 10 cluster centres $c_0, \ldots, c_9$ in the cube, e.g. from K-means, then classify a new ...
194 views

### Active learning for inferring a convex optimization formulation

I was wondering if anybody knows of any relevant references on the general topic of active learning for gradually inferring/updating a convex opt. formulation. As a specific example, I am thinking ...
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### Universal Function approximation

It is known via the universal approximation theorem that a neural network with even a single hidden layer and an arbitrary activation function can approximate any continuous function. What other ...
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### Reinforcement Learning and Optimistic Decisions

Sutton recommended using an optimistic heuristic on decision making by considering the upper bound of the confidence range of an action-value. From my testing, it seems to work. I find this ...
254 views

### Higher-order and black-box clustering

As far as I understand a large number of clustering problems can be formulated as: $\underset{\textbf{P}}{ \text{argmin}} \; \sum_{i,j} f \left(x_i, x_j\right)$ where $\textbf{P}$ is a partitioning ...
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### Genetic Algorithm to Draw a Graph? Position assignment problem

I have an assignment problem at hand and am wondering how suitable it would be to apply local search techniques to reach a desirable solution (the search space is quite large). I have a directed ...
378 views

### Can you make a different learner?

My questions are: [Solved by Dave] Given a learner N, can you design a learner M that behaves differently from N? No. and [Solved by Dave] Given a learner N, can you design a learner M that is ...
174 views

### Does a multilayer perceptron taught by simple backprop learn the shape of a character or the exact image of a character?

(Feel free to suggest a better title) (same with tags, none of relevant tags exist yet, and I only have 101) Let's say I have a perceptron with an optimal number of layers and optimal number of ...
396 views

### Agnostic PAC sampling lower bound

It is well-known that for classical PAC learning, $\Omega(d/\varepsilon)$ examples are necessary in order to acheive an error bound of $\varepsilon$ w.h.p., where $d$ is the VC-dimension of the ...
610 views

### Quantum PAC learning

Background Functions in $AC^0$ are PAC learnable in quasipolynomial time with a classical algorithm that requires $O(2^{log(n)^{O(d)}})$ randomly chosen queries to learn a circuit of depth d . If ...
143 views

### Optimal payoff from sampling from a collection of Bernoulli random variables?

Suppose I have several Bernoulli random variables, $\{X_1, \ldots, X_k\}$, each of which has a fixed probability $p_i$ of equaling 1 for each sample. Further suppose each $p_i$ is randomly distributed ...
422 views

### Support Vector Machines and privacy-preservation

suppose we have data matrix A m-by-n (m observations and n features) which I want to Apply SVM on it achieving privacy (Privacy-Preserving SVM) the questions are:- 1 - Is applying kernel trick ...
281 views

### Using Graphs/Graph Similarity as Features for a Learner

I'm working to construct a learner than can recognize whether two vertices in a property graph (digraph, vertices and edges can have arbitrary keys/values) modelling a social network in fact represent ...
359 views

### Clustering of letters - what approach would give the best results?

I am working on letter recognition program. I have a text and divide it into letters, every single letter is written to separate file. Now I want to apply a clustering algorithm to these images to ...
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### What is the tradeoff between population size and the number of generations in genetic algorithms

Genetic algorithms evolve in fewer generations with a larger population, but also take longer to compute a generation. Are there some guide lines for balancing those two factors, in order to arrive at ...
412 views

### Results on universal approximation for learners other than ANNs

I have an applied machine-learning and statistics background, and when I read the Universal approximation theorem, which (in the context of the learning theory of ANNs - Artificial Neural Networks) ...
207 views

### A PAC-like analogue for 1-class classification?

This is more of a philosophical question -- I am looking for a reasonable mathematical formulation of 1-class learning. In the PAC model, it's very natural to formulate our demand on the learner: ...
317 views

### What machine learning classifiers are the most parallelizeable?

What machine learning classifiers are the most parallelizeable? If you had a difficult classification problem, limited time, but a decent LAN of computers to work with, what classifiers would you try? ...
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### Computational complexity of learning (classification) algorithms - fitting the parameters

My wish is to describe the time complexity of several classification approaches. For example, suppose we have $n$ data points in $m$ dimensional space and a binary class variable. We do not assume ...
2k views

### Find sentences with similar relative meaning from a list of sentences against an example one

I want to be able to find sentences with the same meaning. I have a query sentence, and a long list of millions of other sentences. Sentences are words, or a special type of word called a symbol which ...
360 views

### K-NN or matrix factorization for discovering correlated features?

I am looking to cluster users together in a database, with each user represented by a number of features that are both discrete and continuous in nature. "Similar" users should be clustered together ...
2k views

### off-policy and offline policy reinforcement learning

What's the difference between off-policy reinforcement learning algorithms and offline policy reinforcement learning algorithms ? Or do they mean the same thing ? thanks
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### Great algorithms, machine learning and no linear algebra

I teach an advanced algorithms course and would like to include some topics related to machine learning which will be of interest to my students. As a result, I would like to hear people's opinions of ...
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### Statistical query model algorithms?

I asked this question in cross validated Q&A but seems that it is related to CS much more than Statistics. Can you give me examples of machine learning algorithms which learn from the statistical ...
347 views

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### What are some real world applications for genetic algorithms?

What are some real world problems that have been solved using a genetic algorithm? What is the problem? What is the fitness test used to solve this problem?