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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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
16 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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32 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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35 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
36 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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15 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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3 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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33 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., ...
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39 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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29 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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37 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
25 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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21 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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20 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
43 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
35 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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13 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 ...
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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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12 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
42 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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63 views

Katz Backoff help calculating alpha

$Pkatz(z|x,y) =$ $P'(z|x,y), if C(x,y,z) > 0$ $α(x,y)Pkatz(z|y), else if C(x,y) > 0$ $P'(z), otherwise.$ $Pkatz(z|y) =$ $P'(z|y),ifC(y,z)>0$ $α(y)P' (z), otherwise.$ ...
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36 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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192 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
38 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
34 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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8 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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43 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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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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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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27 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 ...
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30 views

Stopping Criteria for ADMM algorithm

In Page 19 of this paper admm_distri_stats, the authors provide one reasonable stopping criteria for ADMM algorithm in (3.12). Can anyone tell me if there is any principle to find the reasonable ...
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13 views

Budget scoring algorithm

I'm working on a free budgeting app that needs to calculate a few summary scores on the data entered. This is for personal budgeting so no need for enterprise size complexity. I have not done any ...
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15 views

MART and GIS within maximum entropy

What is the difference between Multiplicative Algebraic Reconstruction Technique (MART) and Generalized Iterative Scaling (GIS) for solving maximum entropy problems? They both seem quite similar. Is ...
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31 views

Algorithm to determine a point in time series data, after which probability of increase in value is very low

I am working with dataset which contains number of movie tickets sold per day. This is basically a count of total number of tickets sold, for a particular movie, for each day after its release date. I ...
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46 views

For a U-shaped distribution, how many results must I verify

--edit-- in plain English. I have a distribution with over a million points between 0 and 1 that is shaped like a U with many values falling near 0 and 1. Each point is SUPPOSED to represent a score ...
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44 views

How do I get initial transition matrix probabilities?

I have to develop a system to detect and prevent bank transactions fraud - just credit card transactions, for simplicity - I'm thinking about using markov chain. How would I get the initial ...
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36 views

Sensor fault detection algorithm explanation

I am attempting to implement a sensor fault detection algorithm from a white paper I found here: http://www.hindawi.com/journals/mpe/2013/712028/ref/ You should not have to read the article to ...
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21 views

Estimating the effect of wrong input parameters in a model estimation

I've got a physical system that detect counts in an array of detectors. In each detector $y_i$ I expect to measure $\bar y_i = f_i(\bar \lambda)+\bar b_i$ counts. $b$ represent the vector of of counts ...
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88 views

Customization of a standard Bell Curve

Hopefully this isn't a duplicate, I've tried to search for similar things, but to no luck. I'm curious on how you would computationally compute a random distribution of numbers that follows a bell ...
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12 views

Optimizing Graph to show areas of improvement

I have a data set that looks like below Bucket: 60-65%, 65-70%, 70-75%...... Days: 22 55 21 Bucket is a % performance and days is the number of days ...
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90 views

Optimization with both L1 and L2 regularization

After doing some research I suppose the hard part is that, L2 regularized problem is often solved by gradient descent, while L1 regularized problem is often solved by coordinate descent. But which ...