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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Approaches to dataset, whose elements have different size
I am working with a dataset where each elements is a square table of size m-by-n, where m (the number of rows) is the same for all the data points, while n (the number of columns) varies from tens to ...
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Trying to write a code that detects a maximum value before a drop off in slope
I'm trying to write code for a force test that will output the maximum force before structural failure occurs. I'm a bit of a novice to python, so the issue here might be something simple that I'm ...
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Seeking guidance on data analysis techniques to estimate project LOE based on numeric counts of outputs produced
I’m looking for some basic guidance on where to focus my research in support of some data analysis I’m looking to perform.
The problem space is identifying a methodology for estimating Level of Effort ...
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What are machine learning algorithms which rank films?
Broadly speaking, there are two approaches to producing lists of the best films: human vs machine curation.
Human curation involves someone, a critic, making decisions and/or creating a canon, based ...
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TreeSHAP algorithm: how do UNWIND and EXTEND work?
In the paper Consistent Individualized Feature Attribution for Tree Ensembles, the authors describe the well-known TreeSHAP algorithm.
It aims to calculate the SHAP values of feature $i$ for all $i$ ...
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What is the most optimal machine learning model/algorithm to create a hangman solver?
Want to create a hangman solver, So what is the best ml algorithm (lstm,reinforcement learning, or etc) to use?
Do suggest any other optimal technique if you know?
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How to split a range of numbers considering other variables as well?
Let's say that I have a vector of numbers and I'd like to split it into 3 most optimal ranges for example, then I suppose I can use k-means or Jenks natural breaks. If I'd like to do the same thing ...
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Difference among ID3, C4.5, C5.0
The C4.5 algorithm uses information gain ratio instead of information gain like ID3, and it also adds pruning.
What does C5.0 add more? Is there any example of code? I looked on the web but there is ...
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Where can I find implementation of the various improvements of K-nearest neighbors (KNN)?
I have been facing some challenges where traditional KNN algorithm perform well. I'd like to explore more advanced knn solutions. While researching possible solutions, I came across a paper titled
<...
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How to predict what someone will order?
Suppose Prof. X goes to a road side tea-coffee shop everyday at 5pm just after his office. After reaching there he tosses a coin, and places his order tea or coffee. The shop owner Y has been ...
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Different patterns in dataset
Suppose some features in a dataset have a linear correlation with the target variable, some have a polynomial correlation, and for categorical features, the target values tend to distribute ...
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Appropriate sample size for prediction algorithm
Our study aims to develop a Random Forest algorithm to predict the incidence of suicidal thoughts, after one year, based on the responses given to four surveys at baseline (time-1). Each survey ...
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An algorithm to detect when the sound is not normal?
I was wondering the following problem: Suppose I have a machine and I would like to record its sound and detect automatically when the machine is going to break. What kind of algorithms are used to ...
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Existence of a "three-point" machine learning model?
I may want to ask if there are studies that exist which utilize a "three-point machine learning model. What I mean by "three-point machine learning model is that it may use several ...
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Understanding the stochastic average gradient (SAG) algorithm used in sklearn
For pedagogical purposes I've been trying to create my own implementation of the stochastic average gradient (SAG) algorithm in a logistic regression framework. Page 10 of the associated paper ...
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In DBSCAN, can the distance between a Noise Point and Border Point be less than Epsilon?
In DBSCAN:
A core point is a point which has at least "MinPts" points inside its Epsilon radius.
A border point is a point inside the Epsilon radius of a core point, but it has a number of ...
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Recognizing and assigning text within similar objects
The first timer in image processing - Pardon my cluelessness.
Suppose I have multiple similar objects (box type) that contain several lines of different text strings. What concept should I look into ...
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Are there any algorithm to generate a set of data that match some statistic requirements?
I was wondering if there are time-efficient algorithms that can reverse the process of basic statistics computation. What I mean is an algorithm that instead of computing the mean, SD, max-min range, ...
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how to predict most frequent purchased item in e-commerce?
i have the following dataset:
witch its market transaction dataset and i need to predict the most frequent purchased items based on transaction history, for example: if sara bought milk and cookies ...
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Regression Algorithm while passing in future values?
Very similar to this question here: https://stats.stackexchange.com/questions/406416/including-future-values-in-a-regression
Is it possible to pass future (expected) values into a regression algorithm ...
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Why does the McCulloch-Pitts Neural net for XOR gate use a hidden layer?
So I am rookie, trying to understand why do we use a hidden layer while making a neural net for the XOR gate?
I have tried doing it in code without using the hidden layers like this:
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Why compare multiple machine learning algorithms and then decide which algorithm to use for fine tuning?
I have a problem.
There is a dataset A, which deals with a classification problem. And for this dataset, several different baseline algorithms have been defined and computed.
In addition, three models ...
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Calculate the top 5 optimal parcel locker cabinet configurations
Dear Data Science community,
I have the following problem to solve and I'd like to learn which algorithm or approach I can use to tackle it. I don't expect a full solution here but I really want to ...
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ML/AI - current algorithm landscape
ML spans a wide assortment of supervised models (k-nearest neighbours, random forests, Naive Bayes, logistic regression, support vector machines, neural networks) and unsupervised models (k-means, ...
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Algorithm Comparison for Influencers Ranking
I am working on ranking social influencers on Instagram according to their influential power with the metrics collected below.
Metrics collected:
username
categories (the niche the influencer is in)
...
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Task Distribution
I would like to distribute tasks (going to companies and signing a deal) to sales representatives based on some condition like company location (is it near the representative's place) or profit of the ...
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Which algorithm should I use to find how similar data points are?
I am working with a dataset where each record is a certain type of trip. For example, one record would have the data points:
number of days of trip
day the trip started
where the trip started
how ...
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Finding the tightest (smallest) triangle that fits all points
I'm supposed to find an algorithm that, given a bunch of points on the Euclidean plane, I have to return the tightest (smallest) origin centered upright equilateral triangle that fits all the given ...
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How to plot the computational graph and derive the update procedure of parameters using the backpropagation algorithm?
Please help me to solve this problem without a code (ps: this is a written problem):
Given the following loss function, please plot the computational graph, and derive the update procedure of ...
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Interpretation of the results of the Elbow and K-means
I have the following dataset (after scaling) which contains 5 features:
:
My objective is to cluster this data using an unsupervised ML model.
After using the Elbow method, I get 2 clusters as below:
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Is SVM a good choice for this imputing a numerical variable?
Let's say I have 10,000 training points, 100,000,000 points to impute, and 5-10 prediction variables/parameters, all numeric (for now). The target variable is numeric, skewed normal with outliers. I ...
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Determine optimal number of layers for a neural network based on the dataset
I have a Neural network architecture where there are N parallel-connected layers (min. 3). Based on the dataset and classes it has, the optimal number of layers differ. Eg. for dataset1 optimal number ...
Karan Owalekar
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Why does my regression-NN completely fail to predict some points?
I would like to train a NN in order to approximate an unknown function $y = f(x_1,x_2)$. I have a lot of measurements $y = [y_1,\dots,y_K]$ (with K that could be in the range of 10-100 thousands) ...
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How to gps data anomaly detection in python
I have gps format dataset lat, lon. I want to detection anomaly using python.
I tested knn, smv, cof, iforest using pycaret. But i did not.
These colors anomlay because the
angle change is too much
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What topic does a "selection" algorithm fall under?
I am looking to develop a simple algorithm that is given a set of 10 vectors for a year from which to predict the "winner". This will be a supervised task where the algorithm will be trained ...
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Yolov5 image detection without segmentation?
I have read a number of papers on Yolov5 images detection techniques. But the papers don't refers to any segmentation step done by Yolov5. While I know that it is not possible to do image ...
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Algorithm/method for grouping items based on their relative distance
I'm looking for a method to classify a set of items based on their relative distance.
For example assume we have 4 cities and we know their relative distance:
city1
city2
city3
city4
0
2.1
2.2
3.4
...
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Tuning a multivariate process automatically
I have a process to optimize which involves multiple algorithms. These algorithms are mostly interchangeable, but can have different performance benefits depending upon the input, and depending upon ...
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What changes is the Neural Network back-propagation algorithm doing on the weights?
I have seen the formula for back-propagation algorithm for neural network error minimization, but I am not quite sure about what changes it is performing on the weights individually.
Let us suppose a ...
user127052
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calculate the VC-dimension [closed]
I have a question about VC-dimension. I have this claim and I need to find out what its VC-dimension is
$ H\subseteq\{0,1\}^n $ collection of Boolean functions over n
In my opinion the answer should ...
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How do I minimizie cost for EV charging?
I want to find a charging schedule that minimize cost of charging an EV.
The main objective is to have a fully charged car for the next morning, but the sub objective is to minimize cost based these ...
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Using MySQL Common Table Expressions to solve the travelling salesman problem
The problem I'm trying to solve is very similar to the travelling salesman problem, where there are many paths between nodes in the database. I've tried to edit my example to fit into this well-known ...
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Which algorithm works well for forecasting sales prediction and the reason to choose particular algorithm?
I am working on a project 'Rossmann Sales prediction', in which I have to forecast the sales of Rossmann Stores. So it is a supervised ML problem. I applied random forest. But then in interviews ...
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Which ML algorithm is best works on text data and the reason behind it? Also, which metrics is used for testing performance of model?
I am working on a project - 'sentiment analysis of tweets.' There are 5 different sentiments - extremely negative, negative, neutral, positive, and extremely positive. So it is basically the NLP ...
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Should deterministic models be trained splitting into train, test datasets?
I'm studying the difference between GLM models (OLS, Logistic Regression, Zero Inflated, etc.), which are deterministic, since we can infer the parameters exactly, and some CART models (Random Forest, ...
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Detecting a Piecewise, Noisy, Linear Signal, with Constant Slope and Changing Y-Intercepts
I am trying to algorithmically detect a 2D linear signal under some noisy data.
It is almost a textbook candidate for Robust Linear Regression, except for the fact that, while the slope remains ...
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Can we say brute-force is completely exploration-based?
My definition of exploration is
[Exploration] refers to searching a much larger portion of the search
space with the hope of finding other promising solutions that are yet
to be refined. This amounts ...
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When should I use 'rbf' and 'polynomial' kernel trick in machine learning algo?
I have a problem about hate-speech classification using support-vector machine algorithm.
The task is to identify the sentence that contains 'positive' or 'negative' sentiment.
Which is the best ...
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Can the 'Rainbow Algorithm' be scaled up and sped up?
What's the proper way to train the algorithm with bigger batches or otherwise speed it up?
The 'Rainbow Algorithm' is a Deep Q, Reinforcement Learning algorithm with two neural networks that I would ...
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Any well documented algorithm/function for previously bought recommendation system
I'm working on a previously bought recommendation system for a project. The list I'm trying to sort is static and does not change over time. Assuming each user purchases different items at different ...
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