An algorithm is a a set of one or more computations that will produce a calculated result. All statistics methods are algorithms. Algorithms can be simple, such as calculating a percentage, or can be very complex and require a computer for fast and accurate results.

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Studying fluctuations in time series

I have some time series to analyze. Given the domain the data is coming from - Time series is supposed to have some fluctuations. A regular periodicity might not be present at all in some cases. ...
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8 views

Thomson/Bayesian Bandit Algorithm

I am looking to use the Bayesian Bandits Strategy to find the best arm of a Multi armed bandit. As outlined in the link, the Bayesian algorithm is Sample a random variable $X_b$ from the prior of ...
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34 views

Grouping Combinatorial Optimization

I a have a real world problem for which I need to create an optimization algorithm. I have a set A, and a group of Sets, lets say 500 sets. I need to find the best combination of them to better ...
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23 views

State Of The Art in Algorithm Performance Analysis

I need to write a short state of the art section in my article that is about performance analysis in multiple techniques (algorithms). The thing is that I have no idea on what can I talk about. I've ...
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1answer
43 views

Algorithm: multi label classification

I am a biologist and I have an algorithm question, I asked on stack exchange but was suggested to come here. Also, I have really tried to explain my problem using simple toy data; note that in real ...
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25 views

Decision tree implementation using ID3 algorithm (C# using AFrog.Net)

I am using ID3 algorithm to implement a decision tree and find an output for a given input query. For this I have a past data set and I am trying to implement the application as this code But ...
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1answer
54 views

Minimum interval such that $X\%$ of intervals will contain $\ge Y$ events

I have a data set that contains the dates and times of purchases. Say I have one month of data for the purchases. I am looking for the interval of time, say 10 mins / 30 mins / hourly, for which 90% ...
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21 views

Algorithm to maximize variance within classes in two dimensions under constraint

I am working on a problem that has two dimensions, A and B. Within the two dimensions, there are 6,140 unique points. Each point has a cost associated with it. I have a total cost that I cannot ...
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4answers
39 views

Common values used for hyperparameter grid search?

When performing a grid search for exploring optimal hyperparameters, what are the typical values, or ranges, that are commonly used for alpha, epsilon, gamma, lambda, C, etc? I'm not focused on a ...
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2answers
26 views

How to cluster the data? [duplicate]

I have a data that looks like below and I want to cluster them. What would be the best algorithm to apply for clustering such data. Thanks
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15 views

How to provide a score value to an image based on pattern information in it?

I have a say 30 two-dimensional arrays (to make things simple, although I have a very big data set) which form 30 individual images. Many of these images have similar base structure, but differ in ...
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1answer
23 views

Prediction of vertex scores in a bipartite graphs

I have a bipartite graph with two sets, A and M, of nodes. Every vertex in M has a score associated with it. I have two tasks: To every vertex a in A, I have to assign a score based on the scores of ...
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2answers
33 views

Relationship between categorical factors

I am not sure what this is called in English, but if we have two categorical factors, we can say that one of them (A) is finer than the other (B) if it holds true that if two observations belong to ...
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1answer
43 views

Learning from clicks on Ads [closed]

I need to build an algorithm that predicts the number of clicks a facebook ad would get in the next 7 days. Based on the given requirements, I prepared a dataset consisting of the following ...
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7 views

Which search algo I should use to find simmilar histograms inside my huge database?

I'have a huge database of about 10^8 objects. Every object contains max. 500 words from a dictionary with 50000 words (BoW). An object from my database could look ...
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1answer
43 views

References for learning about online random forests

I am new to concepts of random forest. Can someone provide relevant sites where I could get learn more about using random forests to learn incoming data like an online algorithm?
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19 views

Reference summarizing various machine learning algorithms' computational complexity

For example, suppose you train a linear regression model using the Normal Equation, on a training set $\mathbf{X}$ containing $m$ instances and $n$ features. The Normal Equation requires computing $(\...
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8 views

Explanation of LOF reachability distance

The LOF algorithm introduced in LOF is an anomaly detection algorithm. In a dataset $D$ with a distance $d$ LOF is defined from the following points: 1) $k-distance(p)$ is the distance of the $k$ ...
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1answer
36 views

Distribution of digit-groups in random numbers

I'm storing files and giving them random numbers as the name, using a 32 bit unsigned range, and writing it as hex. Eg: 087b8a08. To avoid having too many files in ...
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20 views

Computing leave-one-out score of the linear regression for a large-scale regression

I heard that, for a linear regression, a leave-one-out cross validation score can be written in an explicit formula (using a matrix multiplication). (I browsed, e.g., http://robjhyndman.com/hyndsight/...
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1answer
42 views

Finding outliers in multiple dimensions

I'm working on dataset which isn't normally distributed. It contains three dimensions: cost, discount and profit. I'm trying to find outliers in all these dimensions. I used $\text{z-score}$ to find ...
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1answer
35 views

Specifying starting values/modes for K-modes Clustering

I have a very large data set with 9000 observations and 25 categorical variables, which I've transformed into binary data and preformed hierarchical clustering and K-modes clustering in R. ...
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2answers
47 views

Interpolating binned data such that bin average is preserved

Say I have this binned data as input. The average value $\bar{y}_i$ is given for each successive $\Delta x_i$ interval. For simplicity, let's assume sampling density is uniform within each bin. Now I ...
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13 views

Finding a number that considers %worse outcomes and %better outcomes

I have a baseline algorithm and lots of test algorithms. The baseline algorithm's performance is compared to every other algorithm. What I'm left with is a table like so: ...
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1answer
28 views

How do I calculate the tipping point of over/under odds in Football?

I am trying to understand how game odds work. One scenario I came across was the over/under scores for football (soccer) games in the form of a table like this: ...
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24 views

Genetic algorithm for solving the un-certain dimension problem

Introduction Last week, I have learned basic genetic programming using Python to solve a simple problem. I introduce it here: There is a city need for air quality monitoring network. The ...
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22 views

online learning- winnow algorithm and mistake bound

I came across an interesting question and I must say I am struggling to figure out how it suppose to work. So we consider the winnow algorithm that learns non-monotone disjunctions. Could someone ...
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1answer
52 views

How to undersample with algorithms in R to solve class imbalance?

My data set is imbalanced - 5% of the target class represents fraudulent transactions, 95% of the target class represents legitimate transactions. I must use the whole data set, as the 95% of ...
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1answer
39 views

Parameters setting in genetic programming to avoid locally optimum

I'm fresh on genetic algorithm. Now, I wrote an python program based on genetic algorithm. The programming contain: Set the population and individuals(For my case, each individual is a list ...
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9 views

Algorithms For ARMA Estimation From Time Series Data

What are some algorithms that can be used to model time series data as an ARMA model? I do not have access to the input process, only the resulting output process as a time series. I don't want to ...
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14 views

Inexact line search in Gradient descent

In general setting of gradient descent algorithm we have, \begin{equation} x_{n+1}=x_n−\alpha d_n, \end{equation} where $\alpha$ is the step size and $d_n$ is the gradient evaluated at the point $x_n$...
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10 views

Full Factorial Help

I have a data set like the following: How can I create a set of scenarios where I reduce column B by the values in Column D and E, in every increment in column F? I also want to make sure that ...
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15 views

DoE and Parallel Coordinate Plot

First off, I'm not too technical; however, I know what I need to do more or less, but don't know how to put the pieces together. I need to create a Design of Experiments, perhaps with R Studio. With ...
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25 views

Calculating error of MCMC algorithms?

If for example the Transitional MCMC algorithm is used (or does it matter which one?), what are the common approaches for calculating an error (some sort of distance from the actual PDF), or ...
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1answer
44 views

Efficient routines for a regression with orthogonal regressors?

I have a standard OLS regression setup, where (sets of) the regresors are orthogonal to each other. I am looking for a fast low-level way (using qr() instead of <...
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86 views

Katz Backoff help calculating alpha

$Pkatz(z|x,y) =$ $P'(z|x,y), if C(x,y,z) > 0$ $α(x,y)Pkatz(z|y), else if C(x,y) > 0$ $P'(z), otherwise.$ $Pkatz(z|y) =$ $P'(z|y),ifC(y,z)>0$ $α(y)P' (z), otherwise.$ $$P'(...
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38 views

Application of Givens rotation to two matrices

I am reading this paper on Multiresolution Matrix Fatorization, http://arxiv.org/pdf/1507.04396v1.pdf, and have come across something that seems like an error to me. In Algorithm 2, the authors take $...
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1answer
201 views

Best classifier machine-learning model for data with few samples [closed]

What machine-learning algorithm do you use if you have an attribute matrix that was rows = samples and cols = attributes and a target vector that matched the attributes to a specific classifier? ...
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4 views

Which efficient algorithms for calculating marginal counts over a complete dataset

Having a complete dataset over a set of discrete variables, I need to compute the marginal distribution over different subsets of variables (For instance all subsets comprising 3 or less variables). ...
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5 views

Sorting algorithm for comparative judgement

I am doing research using Adaptive Comparative Judgement where I present the user two things and let them choose which one is more difficult for them to understand. For now I am thinking of testing ...
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1answer
42 views

Creating a machine learning algorithm [closed]

I've heard of various different types of machine learning algorithms such as logistic regression, neural networks, naive bayes etc, and I was wondering what goes into creating a machine learning ...
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1answer
35 views

Data Transformation or algorithm for prediction of data between 0 and 1

I am trying to predict a time series where every data point is a percentage value between 0 and 1. Most data points are either 1 and few below 0.5. In such a case what could be suitable data ...
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9 views

TF-IDF for matching 2 titles?

My question can look irrelevant. But I guess, it's better to ask here, rather than on StackOverflow. Let's consume, we have 2 long titles, like: ...
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22 views

Special case of clustering in one dimension

Given an array of positions in an X-axis and each position is associated with a Group. An Example is given below: ...
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46 views

Weighted arithmetic mean's alternative for ranking items

I have a Blog post ranking algorithm which has 5 factors which are considered for calculating final score. I have predefined input range according to which i decide score of a factor. e.g. Factor : ...
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14 views

Database and Data Waehouse design and processing in Big Data

With the growing popularity of Big Data and related tools, I am looking for books that specifically deal with implementing a warehouse in one of Big Data technologies, database and data-warehouse ...
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0answers
14 views

Figuring the algorithm / common calculation on a set

I have a column that is size in MM and another that reflects the change in price for said size. I'm trying to figure out the algorithm/common calculation behind these generated numbers so that I would ...
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0answers
8 views

Soundness and history of a significance index comparing different computational realizations

When comparing filtering algorithms, for instance, one sometimes tests deterministic clean data, adds realizations of noise, and measures the residual noise, since the clean data is known. A standard ...
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29 views

Fitting a glm in practice

This question will be a little wordy - I'll try to summarize at the end. I'm currently working on a machine learning library and I'm implementing GLMs. To fit my models I've been implementing an ...