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An unambiguous list of computational steps involved in finding a solution to a class of problems.

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44 views

Which methodology/algorithm can be used to complete this 'fill in the blanks' problem?

I have 'n' realization of some phenomenon (historical observations). From the image below, blue cells represent observing a specific event and the white cells represent not observing the event. The ...
2
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1answer
35 views

What is it called to classify easy inputs before hard ones?

For classifying a lot of inputs, it may be useful to handle the more unambiguous cases first and learn from them before tackling the harder ones. This is certainly how I personally grade student work; ...
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11 views

Regression trees and choosing threshold values to minimize mean squared error

I'm trying to learn a decision tree for a regression problem. Each node of the generated tree, will split by the criterion variable < threshold for some ...
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0answers
16 views

Can someone verify if the following Bayesian Information Criterion (BIC) model selection algorithm is correct for Gaussian mixture models?

I am trying to find an automated way of picking the number of clusters $K \in \mathbb{N}$ for unsupervised learning scenarios, specifically for GMM. I was suggested to use something called the "...
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0answers
13 views

what is apriori algorithm? [duplicate]

what is the apriori algorithm? Apriori is an algorithm for frequent itemset mining and association rule learning over relational databases. I see the details on this page. https://t4tutorials.com/...
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34 views

Why is Rademacher complexity defined the way it is?

For reference, this is the definition of empirical Rademacher complexity from Foundations of Machine Learning (page 30): Let $\mathcal{G}$ be a family of functions mapping from $\mathcal{Z}$ to $[...
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15 views

How does QSVM algorithm differs from SVM?

Where does the working of QSVM differs from classical SVM ? And how it is fast ? During which steps of the algorithm do they differ ?
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1answer
81 views

Why am I getting accuracy of 100 percent using SVM

I am working on Credit card data set for fraud detection. When I apply SVM for it, I am getting the accuracy as 100 %. What might be going wrong here? Here is the code ...
3
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1answer
41 views

Reducing the dataset size for KDE

I have GPS data, so 2 coordinates, and I want to estimate the busiest places (i.e. the places with more data points). However, I have a lot of points: currently ~4 million for 12 days, and I will be ...
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0answers
9 views

Detect swing high and low in set of price [duplicate]

I have set of prices which when plotted in line graph looks somewhat like this , How do I find the prices in the place where I marked red arrow. Any algorithmic/mathematical Idea will be really ...
3
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1answer
24 views

Divide Minimum Spanning Tree into Equal (Disconnected) Chunks

Does anybody know an efficient algorithm for dividing Minimum Spanning Tree (MST) into equal in size disconnected sub-trees? I'm not saying that it is a particularly hard task, but maybe there exist ...
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19 views

How to understand 4 steps of Monte Carlo tree search?

From many blogs and this one https://web.archive.org/web/20160308070346/http://mcts.ai/about/index.html We know that the process of MCTS algorithm has 4 steps. Selection: Starting at root node R,...
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118 views

Simulated Annealing vs. Basin-hopping algorithm

I was planning to use Simulated Annealing algorithm (scipy.optimize implementation) to optimise my black-box objective function, but the documentation mentions that the method is Deprecated in ...
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1answer
60 views

Learning problem when we have data from distributions $(p_i)$ when we care about (known) distribution $p^*$?

Suppose we have a dataset $D$ or multiple datasets $(D_i)$, with distributions $p_i:X\to \mathbb R$. Suppose there is another distribution $p^*$. All distributions are known, including $p^*$, but the $...
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2answers
33 views

Simulating the sum of random dice roll without a loop

I want to perform a random roll of $n$ $k$-sided dice (with values $1$ to $k$), where only the sum of the consecutive rolls is the output I want to get. Assuming I have a (pseudo-)random number ...
0
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1answer
25 views

How to determine decay rate?

Three decay solid lines are plotted in the graph below. They are sqrt(1/n), sqrt(log(log(n))/n) and sqrt(log(n)/n) respectively. I plot my dataset on the graph as the hdi dashed line. How to ...
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0answers
12 views

Is there a way to use HDBSCAN to fit on batches?

I would prefer to use a DBSCAN like algorithm that supports batching data. I can use minibatch k-means but that would require a lot of additional work for optimal performance that HDBSCAN takes care ...
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2answers
79 views

Why can't algorithms avoid overfitting themselves?

So, I understand overfitting (bonus question: precise statistical definition of overfitting?). You don't want to match the noise in your sample. What I don't understand is why this requires a ...
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0answers
38 views

A trivial question about EM algorithm theory

In "The EM Algorithm and Extensions", second edition, from Geoffrey J. McLachlan and Thriyambakam Krishnan, X is the latent variable, and Y is de observed (incomplete) variable I'm little confuse ...
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14 views

Sampling without replacement — method A or method B? Proof?

I have a question combining some stats, probability theory, and presumably CS/algo complexity (weak area for me). We got into a little debate here in the office on the solution. I've done some ...
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0answers
43 views

What's the point of Gibbs Sampling? [duplicate]

I am reading a book on doing Bayesian Data Analysis. I have just learned what the Metropolis Hastings (MH) Algo does, at least in relation to Bayesian Data Analysis. My understanding of the MH Algo ...
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1answer
27 views

Self-organising Neural Network - Looking for litterature

I am looking at developing an algorithm that would automatically grow the structure of a neural network by adding/deleting units within a layer, or adding layers as necessary. I researched the topic ...
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1answer
20 views

For very basic Metropolis Algorithm with one parameter, what happens when you are at the tail?

I'm not sure how to phrase the question, but let's say you are running the Metropolis Algorithm and the distribution you are trying to produce is just a single distribution. Let's say the values of ...
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17 views

Probability that output is result of the same process?

I've developed a simple Monte-Carlo simulation. Output of this simulation is a histogram. This histogram is possibly a log-normal distribution, but I don't want to assume that. But I do know that the ...
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1answer
26 views

Clustering using histograms

I need to find clusters in a very large amount of data (>2M data points), and I was looking for ways to speed up the usual algorithms, i.e. k-Means, DBSCAN, ... Is there any major issue, especially ...
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1answer
27 views

Paired t-test between different algorithms: Properties of paired t-test

Suppose, Accuracies are: Algorithm 1: 87% Algorithm 2: 86% Algorithm 3: 88% Paired t-test value between Algorithm 1 and Algorithm 3 is p = 0.44 Paired t-test value between Algorithm 2 and ...
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1answer
267 views

when to say that an algorithm is a learning algorithm?

If I have an algorithm that deals with data, and the result of this algorithm is binary classes, When can i say that this algorithm is a classification algorithm ( machine learning algorithm)??
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45 views

Is studying Machine Learning really just learning a bunch of algos? [closed]

I've been watching some introduction Machine Learning videos just to see what it's all about and so far my takeaway has been that it just involves learning a bunch of algos (regression, k means, ...
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40 views

incremental $R^2$ update at every new sample [duplicate]

I am sampling from a random process $X$ and I would like to calculate $R^2$ for the cumulative sum of the samples: $$x_1,..x_n$$ $$y_n=\sum_0^n x_i$$ $$R^2_n=RSQ( [1,2,...n], [y_1,y_2,..,y_n])$...
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29 views

Optimal value for multiple input

I run an experiment in which every second I record values of area, circularity, and elongation (there will be probably more variables in the future). I want to find in which second there are the ...
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0answers
7 views

unknown parameters α0 and co-variance matrix Q using EM Algorithm for ddhazard model

I am working on panel data with catagorical variable as independent and 6 explanatory variables. sample years are 1992-2018(27).total number of firm-year observations are 33946. I want to know the ...
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1answer
31 views

How can we conclude that an optimization algorithm is better than another one for a problem at hand

When we test a new optimization algorithm for a particular problem at hand, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,...
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13 views

Is there any algorithms/models to generate embedings of sequential data (other than RNN)?

I know that RNN can be used for such task. For instance facenet used rnn with triplet loss. But maybe there are some less sophisticated alternatives to try first?
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16 views

Nomeclature question for time-series

tl;dr Can you help me relate these acronyms to actual algorithms for time-series classification? Background: I have been looking around in "http://www.timeseriesclassification.com/" and would like to ...
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1answer
80 views

FindSimilar items in a complex dataset

Im a MachineLearning newbie, but I want to learn more about this interesting topic using a practical example, on which I would appreciate any theoretical and practical help: I have a database of "...
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24 views

Is Squeeze and Excitation Network a deep attention model?

Is the squeeze and Excitation Network a deep attention model?
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21 views

How to name a machine learning algorithm where we used very small amount of labeled data?

I have to describe a machine-learning algorithm that needs only very small dataset. I cannot say it is unsupervised because I already used the labels in the training. Also, I cannot say semi-...
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13 views

When combining many algorithms, what are the techniques used to decide which algorithm is working ok and which one isn't?

There are some "technologies" like: Elastic X-Pack Darktrace These use many unsupervised algorithms to find anomalies. As expected, algorithms do not agree on what are and what aren't anomalies. ...
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13 views

Learning rate Adam Algorithm [duplicate]

Finding the 'optimal' learning rate for regular gradient descent is generally a pretty important task, as it could influence the results a lot. I was wondering whether this is the case for the ADAM ...
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1answer
50 views

K-Means clustering: optimal clusters for common data sets

I use scikit-learn to get IRIS and WINE clusters for evaluating an algorithm for K-means clustering. The K-means algorithm is a heuristic algorithm for solving the "minimum-sum-of-squares-clustering (...
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0answers
54 views

Estimating the range of $1$'s in an array of $0$'s and $1$'s

I have a large array $A$ that contains something like $[0..1..0..]$. It has a continuous range of $0$'s, followed by a range of $1$'s, and then another range of $0$'s. This array is large and access ...
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1answer
23 views

Good metric to assess error in estimating a value

So this seems like a simple question, but I cant find a way to solve it or formulate a solution that makes sense. My case is that I have an algo that detects fuel theft (ft_calc). Now I want to ...
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0answers
27 views

STL + ARIMA (2,1,2) equation or algorithm

I have found all questions through this portal. I am very thankful to this community. This is my first post. This time, I did not find precisely the following question: how is the algorithm built of ...
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1answer
36 views

What is the method should I use to calculate similarity in a data set with outliers that must be included?

Information: So I have a data set with 18 vectors with 167 components, each of with has a value with a range of $[-2, 2]$. I am trying to calculate the similarity between one arbitrary vector in ...
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1answer
43 views

Decision Trees - how does split for categorical features happen?

A decision tree, while performing recursive binary splitting, selects an independent variable (say $X_j$) and a threshold (say $t$) such that the predictor space is split into regions {$X|X_j < t$} ...
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0answers
32 views

Minimize element-wise distance between two sets of points in R^n

Given two ordered sets $X, Y$ each containing $m$ elements in $\mathbb{R}^n$, I'm looking for a permutation $\sigma$ of the second set that minimizes $$\sum_{i=1}^m \lVert X_i - Y_{\sigma(i)} \rVert$$...
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3answers
84 views

What kind of statistical model I should use?

Here is the project that I'm currently working on it and would be more than happy if I can get your opinion about it. The project is about dispatching the EMS helicopters to the incident locations to ...
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0answers
14 views

Dynamic Time Warping - building a distance matrix with any distance that we want?

I am new to Dynamic Time Warping. I understand that we build a distance matrix and then try to find the cheapest path from starting to ending point. Typically euclidean distance is used to calculate ...
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2answers
38 views

How to classify time series trends into 2 groups: “contain seasonality” and “doesn't contain seasonality”

I'm optimizing prediction model for time series data trends. Each trend may have seasonality effect or may not. I want to classify each trend into one of the following groups: "seasonality" or "no ...
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0answers
5 views

How to handle unknown terminals in lexical parsing? how to smooth unknown terminals?

I have a treebank of setences. I derive a PCFG from the treebank and with MLE the probabilities of each rule. with those rules and probabilities I'm using CYK parser to get the most probable parse ...

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