Questions tagged [supervised-learning]

Supervised learning is a type of machine learning algorithm that learns a mapping function y = f(x) between input variables (x) and output variables (y). The two most common supervised learning tasks are classification and regression.

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Knowing Joint probability distribution between feature-label space

I am doing a course CORNELL CS4780 "Machine Learning for Intelligent Systems". you can find the link here for the one I am going to refer 1st lecture The professor explains, we have a sample $D ={...
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From unsupervised to supervised in fraud detection

I have a question. I am working on the fraud detection domain. And I have data from imports to the country. As you can get from the title, I have unsupervised data. I do not know that the record is ...
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What would I prefer - an over-fitted model or a less accurate model?

Let's say we have two models trained. And let's say we are looking for good accuracy. The first has an accuracy of 100% on training set and 84% on test set. Clearly over-fitted. The second has an ...
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19 views

When unsupervised learning is more beneficial in comparison with supervised learning even the labelings are existed?

When unsupervised learning is more beneficial in comparison with supervised learning even the labeling are existed? If there is no labeling the unsupervised learning is better than supervised learning ...
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Classification when variables are in ranges

I want to classify my data and some of my variables are ranges. I classify location so for example, school, the hours that people are at school are from 7:00 to 14:00, some of my variables are ...
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Interaction with unseen data (Generalization and evaluation the performance on unseen data in supervised and unsupevised learning methods)

How to generalizes model and performs on unseen data for a highly imbalanced binary classification problem (99.827%,0.173%)? 1-When using supervised learning methods such as logistic reg, RFs, ...
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1answer
32 views

Can we apply to GridSearchCV to Logistic regression .?

When I apply GridSearchCV to my model Logistic Regression, it's continuously throwing below error. I understand that it's trying to convert string to float. But that's was my data. So how can I ...
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23 views

Is pattern recognition the same as unsupervised learning? Is machine learning the same as supervised learning?

Firstly, here is the definition of a well-posed learning problem: A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its ...
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24 views

What is the difference between all the different types of learning within machine learning?

This is a question that is really hard to google, and the differences are confusing. Does anyone have good examples of the differences between them all? Supervised Learning Semi-Supervised Learning ...
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45 views

How to apply Machine learning model on time series to predict next time step

I have done feature engineering on a single variable time series data (spare parts usage), then I turn the time series data into supervised machine learning problem. I have trained and test on the ...
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23 views

2nd, 3rd, Nth closest guesses

I have used the KMeans algorithm to create an engine that can guess the cluster that a particular set of input data will fall into. Can I use it to guess the 2nd closest cluster, 3rd closest, and so ...
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What is the approx minimum size of dataset required to build 90% correct model?

I am working with a financial dataset size which is around 3000. I have attempted the supervised-learning regression techniques and not able to go beyond 70% accuracy. Features: 10 Data size:3700 ...
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41 views

Time Series Generation - Multi Dimensional Time Series Data

Disclaimer: Mathematicians please don't be mad at me for the use of some of the terminologies in this post. I am an Engineer. :-) Background: So I am currently working on a problem where I have to ...
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Mixing unsupervised and supervised algorithms in image classification model

I am trying to replicate the general image classification model used in a paper that I cite later below. The following image is an extract from a paper that proposes a novel method of performing image ...
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2answers
34 views

Is it a best practice to exclude retweets from the data set?

I am going to build machine learning algorithm to identify fake tweets. The data set has huge retweets which I think might be an issue. Do you think given that the focus is the original tweet, it is ...
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Reshape Time series data for Conv2d Block

I am modelling my time series data into a supervised learning problem for the input to a conv2d block in pytorch from this tutorial. ...
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28 views

Extracting Features for Graph transformation

Suppose I have a directed graph G (V,E) whose transformation is defined by a library of patterns. Each vertex is of particular type. The library of patterns contain subgraphs (g1,g2,g3 etc)and it's ...
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37 views

Doing predictive modeling on predicted value

It's a project that I'm working on. Here are the steps I took: I want to make a recommendation service based on the customer data. I first used a collaborative filtering method to get the recommended ...
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2answers
148 views

Suggestion for stacked modelling in machine learning

I have built several models on the training dataset and i am not happy with the results and I wish to club them all together and generate a new model, so here is my idea as i already have the results ...
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Underfitting: Kernelizing and Optimazing

Today I was at a research conference and I have question what is meant with this: What does it mean to better optimize a supervised classification machine learning algorithm in combination with ...
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Is it wise to include the target labels when a supervised learning problem is tackled as an unsupervised learning problem?

I have a problem which requires both a supervised and unsupervised learning approach. This is because I am trying to find some hidden clusters (if they even exist) beyond the labels of the dataset. ...
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Predict the mistakes of my Model?

This is in the context of trading software: Let's say I am party A that is analyzing historical data of stock shares. Based on these historical data I want to decide whether I should buy a stock or ...
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1answer
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``Hierarchial features extraction'' in Multilayer Perceptron models

I am referring to plain neural networks, MLPs. I got to read the paper by Glorot and Bengio (2010), Understanding the difficulty of training deep feedforward neural networks. Therein I read an ...
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Dataset Image creation suggestions

I am trying to create a dataset where the Text is mixed, e.g. " I love football" can be written as " I l()v3 F00tba11". The idea is that by using Tesseract I can find the pattern to match these two ...
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3answers
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Supervised clustering

I'm working on a clustering problem. I have a training set composed of sets of points where the clusters are known and I want to find the good clusters on a testing dataset. It's a kind of supervised ...
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1answer
23 views

Supervised Learning: time estimation of bike repair

I would like to train a model that estimate the time a given shop would take to repair for a bike using the data below: shops.csv ...
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1answer
26 views

How to train a Machine Learning model for blocked data

I'm concerned with a supervised classification problem for the following type of data. The data consists of $N$ rows (where $N$ is not very large - this is not a big-data problem) and $M$ columns (...
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Scikit learn - best model to classify supervised two-feature data?

I'm quite new to scikit learn but I am looking for the best approach to go about classifying some data I've collected where each set contains two measurements made over several points of time, along ...
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How to check if a class segmentation is meaninfull?

Using the Lending Club dataset I have a data frame with the loan characteristics of some borrowers. Here is the distribution of the subgrades: ...
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2answers
92 views

How to represent audio data in a format that can be used for preprocessing and modelling?

I have a project that I am working on currently. The project is to classify audio data. The data is in two folders train and test...
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1answer
12 views

adding non-failure data to failure one

I have a dataset containing features of different engines showing when they failed. I want to build supervise learning model to predict whether an engine with a certain mileage is going to fail or not....
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3answers
101 views

Why models performs better If normalize test data and train data separately?

Many threads (and courses) such as this and this one suggest that you should apply normalization to the test data using the parameters used in the training set. But other some discussions I've found ...
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2answers
104 views

Why is there a trade-off between bias and variance in supervised learning? Why can't we have best of both worlds?

The bias-variance trade-off is like a law in machine learning. You cannot have the best of both worlds. What is it about supervised learning in machine learning that makes it impossible to satisfy the ...
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1answer
279 views

svm.LinearSVC: larger max_iter number doesn't always increase the accuracy/precision/recall

Background: Supervised machine learning Data shape 10+ features, target = 1 or 0 only, 100,000+ samples (so should be no issue of over-sampling) 80% training, 20% testing train_test_split(X_train, ...
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Using Unsupervised / Supervised Learning for RGB manipulation

I need to teach a model(or any substitute) for automatically adjusting the concentration of R, G, and B values until they make up white colour. i.e, tweak the RGB values (beginning from some arbitrary ...
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1answer
27 views

Predicting probability for each tag given already chosen tags

I have a set of tags (~10'000, will be extended over time) presented to a user. After he has selected 3 or more tags, I want to predict for each remaining tag what the chances are that the user will ...
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1answer
19 views

Very simple real-valued time-series dataset for RNN prototyping

Is there a simple real-valued time-series dataset on which a vanilla RNN model can be trained. With "very simple" I mean only two to four real-valued inputs per time step and a single real-valued ...
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49 views

Is there a way to use Plotly as an annotation tool, for labelling time-series for instance?

I have been tasked to create a tool aimed at labelling sections and/or precise data points of a biomedical time-series. Our main framework is written in Python. I would like to know whether it is ...
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1answer
23 views

Algorithm for user profiling without distinct profiles

I am trying to design an algorithm that takes in a new user with the variables department, location, job_role etc. and I want a machine-learning algorithm to decide ...
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3answers
59 views

How do ML model retain/store the learning(s)?

In other words, if the model after training and testing is ready for making future predictions, it must be storing the learning(s) somewhere in memory or disk or cache (or I really don't know). So, ...
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1answer
862 views

XGBOOST : model.predict_proba() and model.predict() conflicting behaviour

I have two classes : 1 and 2 The output of model.predict_proba() -> [0.333,0.6667] The output of model.predict() -> 1 This is happening for around 200 test values out of the test data of 10 lac. ...
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1answer
47 views

Super Resolution CNN vs Regular CNN

I am digging into finding a solution for background subtraction and one of the requirements is to not loose in quality of input image. Found that there is a specific type of CNN like Super Resolution ...
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30 views

suitable algorithms for very high dimensional ”binary pattern" recognition?

I have a dataset consisting of 3000 binary features and one binary ouput. subset of these binary features form binary patterns. these subsets could be neighbouring features or from different regions (...
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1answer
48 views

Which feature to use in feature selection?

Objective: Multiclass classification with supervised learning, small dataset (25h) Context: My dataset is composed of mobile network data collected with a smartphone. The labels correspond to the ...
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60 views

Supervised Learning Quiz website?

What are some good websites which provide quiz questions on supervised learning and machine learning in general? I have a quiz coming up and I would like to be prepared for it.
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Why does feature scaling improve the convergence speed for gradient descent?

From this article, it says: We can speed up gradient descent by scaling. This is because θ will descend quickly on small ranges and slowly on large ranges, and so will oscillate inefficiently down ...
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Extract data from mainly unstructured sets and derive risk metrics out of those

I have the following question (this was a real life example): Q: Extract data from mainly unstructured sets and derive risk metrics out of those. From what you know or imagine about the data ...
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19 views

How to use fresh data when target prediction period is long?

I'm using supervised learning on monthly activity data to predict when a customer buys a particular product. This product is typically bought infrequently and at the moment my target variable is ...
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1answer
36 views

Is there an algorithm for categorizing unlabeled samples into K classes? [closed]

I am not sure if this would be considered unsupervised, or semi-supervised learning. I am looking for an algorithm that will take N input arrays of features, and then cluster samples(not features) ...
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How do I use the supervised learning classification in my project? [closed]

Just to give an idea of what I'm doing: I'm doing a project with financial data (tick data) and I'm trying to create a way make a model learn what happens before a breakout. Usually there ...