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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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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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24 views

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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How to A*-search algorithm in path expanded? [closed]

What the theory of A*-search while expand path? f(n) = g(n) + h(n) if path complete, but have value bigger than path which not complete. what a path still ...
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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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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
52 views

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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1answer
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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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Data Grouping by Three Characteristics

I've got an interesting question: I'm building a system that will be handed data in a specific format. It's a part of a Quality Control system, but this system also packages these "widgets" together....
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How to Compute Multinomial Naive Bayes likelihood

I'm following this tutorial to implement a Multinomial Naive Bayes classifier to categorize text documents. It works to identify 1 single class, but how could I get the likelihood of a sample to be of ...
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1answer
25 views

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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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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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
170 views

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
59 views

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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27 views

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
38 views

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
41 views

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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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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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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63 views

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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1answer
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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 ...
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automatic multi data Segmentation modelling?

Not sure which tag I should use here. I went to a presentation by a company last Friday who provides deep learning solutions for banking, marketing etc. In that meeting, the sales guy say that they ...
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CNN combined with a competitive search algorithm [closed]

I'm reading some papers about Deep Neural Networks applied for board games, like for Go with AlphaGo, AlphaGo Zero and some other games, like Othello and Chess. Most of the works are using CNN's as a ...
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2answers
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Identify objects (bus) on the map based on coordinates (lat, lon) [closed]

Let's say I have an android app that frequently sends current GPS location of the user. If person is driving with bus, I can easily get GPS location of the bus and display it on the map and update it ...
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2answers
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Prediction in Machine Learning

When we use a regression algorithm in out dataset it's because we assume that there is a relation between our input data and some quantitative value. This is expressed as : $y = f(x)+\varepsilon $, ...
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2answers
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Regression - random error term

When we use a regression algorithm in out dataset it's because we assume that there is a relation between our input data and some quantitative value. This is expressed as : $y = f(x)+\varepsilon $, ...
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1answer
51 views

Predict ratings for Item Based Collaborative Filtering

Given the (cosine) similarity score of top 100 neighbors of every item, how do I predict ratings for unrated items? Please explain in simple terms. Item 1 260 0.577305 780 0.5655413 1210 0....
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Estimate battery voltage based on scheduled events and previous behaviour

My goal is to estimate if a battery will have enough charge for certain other systems to be powered. The power state of the other systems is recorded (i.e. if they are turned on or not), as well as ...
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1answer
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Algorithm for multiple input single output ML

As an ML newbie, I have a question. I have a set of data with 2 inputs and 1 output. I'm trying to predict the output. input1 is an integer number, input2 is like a category between 1-5. Output is ...