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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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Clusterise 2 variables in 3 groups

I have thousands points for 2 different variables i would like to clusterise in 3 groups : -1, 0, 1. If i drop the group 0 in my dataframe and scatter plot for -1 and 1 i have the following : It's ...
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support vector machine under noisy labels

I am relatively new to machine learning and had just read the SVM chapter in the introduction to statistical learning book. I am interested in applying SVM to my data. In theory, my data is perfectly ...
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How to visualize image segmentation results

I am using u-net to do semantic segmentation for N>1 classes. The input size is (128,128,3), the output size will be (128,128,N). what is the correct way see the prediction as an image ot size n1 x n2 ...
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True value functions fitting in NN

We need to approximate a function by the neural network. Input parameters are normalized. However values of this function are large on the considered domain so that NN just does not converge via « ...
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Dataset for ML project: Application of Machine Learning to improve breast cancer treatment

My issue in relation to finding the right dataset for my current project. I visited the cancer imaging website to find some data for investigating my hypothesis [which is " denser breast tissue (fibro-...
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How to identify/Analyze HOG feature data is linearly separable or not?

Work Objective: I am working on Object tracking, I have extracted the Feature vector for ROI(Region of Interest)/template from Image, using this features i am looking to identify most probable ...
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Looking for freely available labelled time series data sets for automated feature extraction and selection

I am looking for recommendations of big, labelled time series datasets that are freely available on the net. My aim is to apply and evaluate methods of automatic feature generation and selection, ...
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Is there any tool for data visualization and manipulation?

I have a time series data set that I need to manually label them for supervised learning. What I am doing now is using excel to plot, and when I see the pattern that I want, I hover over the data on ...
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Performance degradation from video compression

I have two datasets. The first are frames saved as pngs (lossless) from a live video feed, and the second are the same frames taken from an mp4 (H.264 compression). Training the same image classifier ...
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47 views

how to build a predictive model without training data neither historical data

I m trying to score "how much a product is expected in the market". I created some features: How much this product is used each year. Where was it used . how many product for each country. the main ...
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Compare job ads with a given set of categories (which each consists of terms)

For a recent research paper, I plan to perform the following, for which I'd kindly ask for your advice. I obtained a set of a few thousand job ads. I now want to analyse how and whether these job ads ...
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35 views

Can preprocessing the whole population cause data leakage?

Introduction I understand the problem of data leakage that could be caused by the preprocessing step when our training and test sets are just samples of an unknown population. The preprocessing ...
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why does ID3 Decision tree algorithm not give the best decision tree?

I was going through ID3 algorithm, and what I believe is it incorporates Greedy Search rule to get come up with the decision tree. If it gives the best split possible at every stage, how does it not ...
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What are the differences between Reinforcement Learning (RL) and Supervised Learning?

What is the difference between Reinforcement Learning (RL) and Supervised Learning? Does RL hava more difficulty in finding a stable solution? Does Q-learning have more difficulty in finding a ...
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Detecting abnormal 'cat' behaviour via Supervised Learning

A few work colleagues and I were looking through a recently replaced 'cat', we had in the workplace. For those of you which are curious, the 'cat' in this context, refers to a specific type of pump ...
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Is max_depth in scikit the equivalent of pruning in decision trees?

I was analyzing the classifier created using a decision tree. There is a tuning parameter called max_depth in scikit's decision tree. Is this equivalent of pruning a decision tree? If not, how could I ...
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Recommending top answerers for a Question on Quora/Stackexchange sites

I want to make a tool that will tell me who can potentially answer a question on Quora or StackExchange. The tool will take input the text of a question, and output a sorted list of users who can ...
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Architecting an Attention network

Given the following data: ...
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1answer
23 views

Which ML algorithm to use if we have categorical data, numeric data, derived data (derived from) other variable in our data set? [closed]

I am a beginner in Data Science. I have a data set which contains numerical data, categorical data and derived data (derived from other columns). The target column (dependent) is binary. Which Machine ...
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Why neural networks do not perform well on structured data?

I was recently working on some classification problem where decision trees performed better than neural networks. I had tried various combinations with neural networks altering the number of neurons / ...
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how to identify the unknown class in machine learning?

In the problem of multi-label classification how to identify the unknown class which is not in training labels or classes. In the prediction phase, the classifier puts the data in any of the class ...
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2answers
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How to check if the dataset contains sufficient information to predict a continuous variable

Is there a way to check if a dataset generally contains enough information to predict a target variable? In other words, can you calculate something like a correlation-coefficient between all ...
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1answer
37 views

bad regression performance on imbalanced dataset

My current dataset has a shape of 5300 rows by 160 columns with a numeric target variable range=[641, 3001]. That’s no big dataset, but should in general be enough for decent regression quality. The ...
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1answer
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ML Models: How to handle categorical feature with over 1000 unique values

I am trying to build an ML Classification model on a data set that contains quite a few categorical columns. However, few of them have over 1000 unique values. I am concerned that if I run one-hot ...
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1answer
76 views

How to automatically verify official documents?

I am new to machine learning and data science. I apologise if the question seems very basic. I have a requirement where I need to verify information submitted via a form with the corresponding ...
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1answer
25 views

Is the neural network in DQN used to learn like a supervised model?

Is the neural network in DQN used to learn like a supervised model?
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2answers
81 views

Is NN with no hidden layer is behave like a regression?

Is a NN with no hidden layer is behave like a regression? What we could say that NN without hidden layer can say us? ​ If we have for instance 20 input and 4 output and I have no true label, is it ...
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Introducing synthetic training observations based in business knowledge

I work for a supermarkets company. My team is building a supervised model in order to predict a new store sales. The idea of the business team is to use the model prediction during the decision ...
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2answers
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Taking Neural Network's false positives as the recommendation system result?

I am creating a recommendation system and considering two parallel ways of formalizing the problem. One classical, using proximity (recommend the product to the customer if a majority vote of 2k+1 ...
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Intuition / Importance of intermediate supervision in deep learning

These days, I have seen many papers using intermediate supervision. Single Network When using a single neural network, multiple neurons output predictions, perhaps by processing data in different ...
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How to define an anomaly detection problem?

I defined a supervised machine learning tasks as: Given: $m$ training examples with $n-1$ features: $E\in\mathcal{R}^{m\times (n-1)}$ and labels: $L \in \mathcal{R}^m$, a model $f$ of $d$ ...
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Random Forest for Edge Detection

Background: This project, Fast Edge Detection Using Structured Forests (written in MATLAB and C++), developed by Microsoft Research, applies random forest to detect edges from an image. The ...
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Relation between query id and feature vectors in pointwise and pairwise ranking approach

I am reading about Learning to Rank and I am not sure how is the data treated during training/testing in pointwise, pairwise and listwise approaches. Usually, I am given a data in a form of relevance, ...
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How to classify a dataset into 5 classes even though the performance is low?

I have a dataset of 5 classes with 8 features, say A, B, C, D and E. Now when I try to classify these into individual classes, I get accuracy, specificity and sensitivity of approx 50-60%, which is ...
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4 Class Classification - Machine Learning Model

I have a data set which contains nearly 150 features and 60k data. And my target feature is continuous variable represents hours. I divided this period into 4 categories of user engagement (4 ranges ...
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How to do feature engineering for email cleaning / text extraction?

I have a large batch of email data that I want to analyse. In order to do that, I need to first prepare the data, as the messages are quite often >80% noise. Generally speaking, my dataset's structure ...
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1answer
381 views

focal loss function help

I am working on a relation extraction and classification problem. The data is in the form of text files. The data is imbalanced. I want to use focal loss function to address class imbalance problem in ...
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1answer
34 views

How to deal with unbalanced class in biological datasets?

When dealing with unbalanced class, which is better, oversampling/undersampling of the classes or randomly selecting equal number of positive samples and negative samples from the training dataset ...
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2answers
37 views

Why does prediction by a consensus of classifier work better than prediction by a single classifiers?

I have seen that consensus of classifiers (taking say 5 separate classifiers) and obtaining the final labeling of the unknown sample based on the voting method (whichever class gets the predicted the ...
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Semi-supervised Learning doubt

I'm reading "Hands on machine learning" by Aurelien Geron. He stated that semi-supervised learning is: Some photo-hosting services, such as Google Photos, are good examples of this. Once you ...
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1answer
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How to show value of a classification model even though it doesn't get the desired performance?

I developed a classification model for a telecom client. Where we classify between Dual-sim and non-Dual-Sim clients. After many iteration the best precision we can get is 60%. The contract says that ...
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1answer
28 views

Is there any work done on reconfigurable convolutional neural networks?

Convolutional Neural networks are used in supervised learning meaning models are always "set in stone" after training (architecture and paramters) so this might not even be possible, but is there any ...
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Function/model aproximation for data with deep ridges/drops

I have five dimensional data: Features a,b,c,d and output "result". Result should be minimized. As you can see in the plot (c vs. b) there are a few deep drops which should be modelized in particular. ...
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1answer
33 views

1 - Nearest Neighbor , dealing with same distance

I know that as a question it may seem stupid, but in case it is applying K NN with k = 1 and I have two neighbors at the same distance , what is the best approach to carry out the classification ?
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1answer
61 views

Graph & Network Mining: clustering/community detection/ classification

I am working on graphs/networks where nodes and edges have some attributes. I want to know what algorithm exist for: 1) clustering a graph to k groups: depend only on the structure (edge attribute ...
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3answers
623 views

Binary Classification

I wanted to start off by saying this is not an exact duplicate of the other question. I checked it and it didn't have what I urgently need. So here is the problem. I have a dataset with 30 features ...
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Concept Learning - Biased Vs Unbiased

I'm new in Concept Learning and I'm reading something about it just to have a greater vision of the different kinds of learning. I understood that the goal is to find the hypothesis h* that fits our ...
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78 views

Machine Learning Algorithm for Dynamic Environments

Which methods are best for managing and predicting and labeling data in dynamic environment? The system data distribution changes and it is not static. The system can have different normal settings ...
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1answer
217 views

What to report in the build model, asses model and evaluate results steps of CRISP-DM?

I would greatly appreciate if you could let me know what to report in the following steps of CRISP-DM? Build Model: what should be reported for parameter settings, models and model description? I ...
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64 views

Clustering of devices in locations?

My question is about using some sort of AI to assess if devices are located in any of a list of venues. I'd ask of machine learning, but so far we're doing this with an expert system, and we are ...