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Questions tagged [algorithms]

An algorithm is 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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Loyalty Insentive vectorization

I am working on an Telecom Loyalty program's insensitive project. Right now I am stuck how to convert a scheme or offer by companies into relevant numerical vector to be fed in some model. I am in ...
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Is there a way (like planning algorithms) to draw a successive polyline to fill a specific shape (like triangle)?

there is a specific shape (like triangle) area, i am trying to develop an program to draw a successive polyline inside the triangle to fill the triangle, one line 3 layers this post demonstrates some ...
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Dynamic discounts e-commerce

I am working for an e-commerce platform that offers discounts to specific merchants or for specific products (sort of affiliate marketing). I would like to implement a dynamic discount algorithm so ...
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What is the name of the prediction method?

Suppose, I have a data set: ix m_t1 m_t2 1 42 84 2 12 12 3 100 50 then, we can calculate the difference between ...
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How to solve a tie in one-r?

when using the one r algorithm with this data a triple tie happens, age group = 10/12, fresh fruit = 10/12 and id = 10/12 why does weka choose age group? Age group: Senior -> Anchovy ...
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clustering people according to answers on survey

Hi I am finding it hard to find online the best clustering algorithm for clustering people according to answers they gave on 20 question survey. There are four categories which each of these answers ...
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Reinforcement Learning - Q Learning - Number of Steps to Decrease?

I have an implementation of the Q-Learning algorithm intended to solve the racetrack problem. I have noticed that the initial amount of steps needed to solve the problem is somewhere between 3000-...
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38 views

K-Nearest Neighbours algorithm explanation needed

I need some explanation for K-Nearest Neighbors algorithm. Why is the training process needed in KNN algorithm? In regression models the training process means to find optimum parameters for a ...
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How to test multiple algorithms at once?

I was wandering if there is a method with Python and/or Sklearn to test multiple algorithms at once instead of run them one by one and see the accuracy. I have been looking on the web and I've found ...
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Estimating location in a model

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are ...
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Is the Apriori algorithm suitable for database tuples?

Problem description: I need to use an association rule algorithm that lets me use database tuples and I think Apriori is a good option, but I am not sure. Starting point: I know the Apriori ...
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1answer
61 views

In which cases shouldn't we drop the first level of categorical variables?

Beginner in machine learning, I'm looking into the one-hot encoding concept. Unlike in statistics when you always want to drop the first level to have k-1 dummies (...
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How to install XGBoost or LightGBM on Windows?

I'm a Windows user and would like to use those mentioned algorithms in the title with my Jupyter notebook which is a part of Anaconda installation. I've tried in anaconda promt window: ...
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Comparing English word pronunciation complexity

I'm trying to figure out a way to compute a score for the pronunciation of a given english word, so I can use that score to compare the pronunciation complexity between english words. Eg: Given ...
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1answer
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Proper Understanding of Condensed Nearest Neighbor

I have a question regarding the Condensed Nearest Neighbors algorithm: Why am I returning Z, which if I understand correctly, is the array of all of the ...
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Detecting seasonality in timestamped events

I have a program that detects events in a large amount of measurement data. When it detects an event, it writes a timestamp. I have thousands of event timestamps. What I wish to do is detect if there ...
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Multiclass classification problem with more prediction classes than real classes

Can I have a multiclass classification problem with more prediction classes than real classes? For example: I want to predict the channel the user is going to watch. The real classes are "user didn't ...
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How to train continuous/soft classification model?

The classic classification problem is like finding the function $F:\mathbb{R}^n\mapsto \{0,1\}$. The label set will be [Apple,Banana,Banana,...,Apple]. What if I want to train a function $F:\mathbb{R}...
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1answer
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ML algorithm with fixed number of inputs and variable number of outputs

I am trying to solve the following problem: Let's say I have a chess position: I encode each square as one-hot encoded vector of length 13 index 0 for empty square index 1 for white pawn index 2 ...
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Adaboost - Show that adjusting weights brings error of current iteration to 0.5

I'm trying to solve the following problem but I've gotten sort of stuck. So for adaboost, $err_t = \frac{\sum_{i=1}^{N}w_i \Pi (h_t(x^{(i)}) \neq t^{(i)})}{\sum_{i=1}^{N}w_i}$ and $\alpha_t = \frac{...
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Feature importance decision algorithms

I have a dataset with 100+ feature columns. My client asked me to choose "the top 10 most important features" from the 100+. From this post, I learnt that Random Forest can help me ranking the ...
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1answer
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Showing the response time on a graph

I have several computing devices. I have used an algorithm to balance the load between these devices. There is a central coordinator which controls the load on each device and if one device is ...
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1answer
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Efficient way to search list of items in a text document

I have a list of items (size ~50K) and several documents( average page per document ~10). I am trying to find what all items are listed in each document as follows : ...
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1answer
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Finding a Data pattern [closed]

I am new to this data science field. I have data of points in 3D space and each point "helps" a metric. I have the sets of points and corresponding metrics. Data might look like: ...
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Dimensionality reduction categories

According to what I found, dimensionality reduction has two types feature selection and feature extraction . In feature extraction, we find PCA, LDA ,LLE , ISOMAP, etc.. In other works i find random ...
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1answer
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Product classification in hierarchical categories based on multiple parameters and non-standard descriptions

I want to start a machine learning project in my company and a really big pain for spend analysts is to classify the products that buyers order for maintenance, tooling, raw material and such, as the ...
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Is there an algorithm for separating/clustering pairs of data so that each member of the pair goes to a distinct cluster?

Basically, I have a giant set of data that exists in pairs (A1A2B1B2C1C2...) and each piece of data has >100 variables. I'm trying to separate that data into two distinct groups, but I don't know ...
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Which algorithm is perfect to determine best fit analyst based on multiple factors?

Assume I have a team of 200 analyst who work on different IT tickets. I want a better ticket assignment system which considers multiple factors before ticket assignment. Outstanding Ticket with each ...
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1answer
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Please help select an Algo based on Accuracy and Confusion Matrix

I am very new to Data Science would appreciate your advice big time. Got a task: predict if a trade will be profitable or not, based on a set of data. I have prepared, cleaned and tested data. ...
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Discrete choice questionnaire construction

I'm trying to conduct my first Discrete Choice experiment. To do this I have to construct a proper questionnaire to measure consumer preferences in a best possible way. The experiment concerns ...
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1answer
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Advice on what Machine Learning Algorithms to study for a Job to candidate matching algorithm

I have asked in a few places and this seems to get down voted for some reason. If this is not the place to ask this then some advice on how and where to ask it would be appreciated. I'm creating a ...
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What is the simplest optimization algorithm for a multi-parameter closed system?

I'm working on a minimization problem for a wireless communication link. I want to minimize the total bit error rate (BER) of a closed system. My problem is that the signal has multiple (50) ...
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2answers
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Choice of ML algorithm for problem

Working on a school project where we have to match some users based on common interests. Assuming I have a list of inputs like this: Name Interest1 Interest2 Interest3 Interest4 Interest5 Name ...
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1answer
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P-value mining on large number of combinations of variables

I really don't know any machine learning, but have a problem that seems like one where I should use some ML algorithm. I am analyzing a medical study with one age-related condition, age, a treatment, ...
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1answer
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Classification vs Regression Algorithms - Should exists algorithms only for Classification and/or Regression

Dummy question: There exists algorithms that should only be used for Classification or Regression problems? For example, should Random Forest should only be apply on Classification problems and ...
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1answer
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NLP algorithms for categorizing a list of words with specific topics

Currently I am using LDA to apply topic modeling to a corpus. Since LDA is unsupervised, it returns a set of words for a given 'topic' but doesn't necessarily specify the topic itself. I was wondering ...
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1answer
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Is the k-center problem part of machine learning or computational geometry? [closed]

I am currently working especially with the k-center problem, which is e.g. used to determine optimal locations for k warehouses. This is done by defining k circles that cover a given set of points (...
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1answer
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Are there any learner-specific optimizers?

In reading about machine learning (ML), and working through some basic examples, it appears to me most learning algorithms use generic optimizers. I am using the word "optimizer" to describe the ...
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Are there any Meta Knowledge bank available?

What resources do you use to learn meta knowledge ? By meta knowledge, I mean generalized information that will help us take more informed decisions when working on a problem later. Example of meta ...
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3answers
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What are the 2 classes of categories to help define a problem

While studying about machine learning, I've learnt the importance of defining your problem before getting started trying to model it. I can see 2 types of problem categorification: Supervised / ...
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1answer
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To which category does this algorithm belongs?

I have came across the Catboost package. Among the classes in categories in Sklearn, Catboost seems to belong to Ensemble methods. What are then the advantages of Catboost over AdaBoost, Bagging etc.?...
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1answer
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Adaboost vs Gradient Boosting

How AdaBoost is different than Gradient Boosting algorithm since both of them works on Boosting technique? I could not figure out actual difference between these both algorithms from theory point of ...
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1answer
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Algorithm Suggestions for a Self Project [closed]

So, I am doing a small self project on data analytics. I am collecting the android apps data from the play store sites by web scraping. I am basically trying to collect all possible information ...
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SVD++ vs wALS: Which is the more effective for implicit feedback in Recommendation system

As SVD++ can be used for implicit feedback, I would like to know whether SVD++ can gives better results than the wALS algorithm (paper: Collaborative Filtering for Implicit Feedback Datasets ). I can'...
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Why do we need a gain ratio

I'm learning about decision trees, and I feel like up till now I've understood them and the math behind them pretty well except for one thing: the gain ratio. As I understand, the gain ratio is ...
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Mean-variance mapping optimization (MVMO) in R

Someone know tell me if there is any package in R about Mean-variance mapping optimization (MVMO) algorithm? I already researched, but don't find anything about this.
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2answers
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Which type of clustering algorithm to use to identify the “same” item in different data sets?

I'm trying to find a solution for a data quality problem - specifically, identifying which items in different data sets are used to represent the same things. As an example, assume that we're a ...
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R codes for “Matrix estimation by Universal Singular Value Thresholding”

Consider a real demand estimation problem of a retailer where matrix Y is the real demand need to be estimated by using sales data (matrix) X which is bounded by stock (matrix) C. The estimation ...
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Statistical Significance in Pairwise Ranking Algorithm

Can anyone recommend an algorithm/toolkit to rank items that have been rated in a hot-or-not style that gives statistical significance? For example, out of a set of N images, two images are shown to ...
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What are non-machine-learning methods called?

For my masters, I'm comparing different approaches to solve a problem (like image segmentation). I'm comparing machine learning and deep learning approaches to «classical» algorithms (like simple or ...