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.

Filter by
Sorted by
Tagged with
-1
votes
1answer
12 views

How to use id's in binary classification problem

I would like to predict for a given user (on a website) if he/she logs out from the website within ten minutes. In terms of data, I have a user ID and timestamp of the latest post on the website. ...
0
votes
0answers
14 views

Example of Reverse KL Divergence in Supervised Learning

It is of common knowledge that Supervised Learning uses forward KL divergence. However, I would like to use Reverse KL Divergence and am looking for examples of similar usage in literature. Most ...
0
votes
1answer
19 views

Exploratory Data Analysis on dataset divided by winners and losers

I have a dataset where I have features from winning tennis players and the other half are from a losing tennis players: ...
1
vote
0answers
24 views

How to detect payment's fraud using Machine Learning?

While browsing Machine Learning problems, I came across this question: "Given a month’s worth of login data from Netflix such as account_id, device_id, and metadata concerning payments, how would ...
1
vote
1answer
31 views

How to set different weights for different training samples?

Suppose that your supervised learning training set is made out of 3 different datasets, merged into a big one. Because of the way each of those was labeled before merging, you might be suspicious that ...
1
vote
2answers
27 views

Input with variable length Classification problem

I have a dataset with patient information with discrete labels (labels are stages of a particular disease) which needs to be predicted (Basically a classification problem). The dataset looks ...
0
votes
0answers
5 views

What methods exist to compare two corpora for suitability of supervised model use?

Whereas so many Kaggle contests I have done have a test set which is withheld from the entire single dataset, often times I find myself asking: if I train a supervised model one this one corpus, how ...
0
votes
1answer
17 views

Which supervised machine learning algorithms assume normally distributed feature variables?

I want to understand the assumptions made by supervised machine learning models. I've heard it said many times that 'you need to make sure your feature variables are normally distributed for your ML ...
1
vote
1answer
39 views

How to train a machine learning algorithm with multiple labels

I have the following challenge and I very much hope that there is a solution to it. I also suspect that there is a simple approach to it. I just don't see it at the moment. Any help or advice is ...
0
votes
0answers
19 views

What ML model should I use for matching 3 datasets on a selection of common columns?

I am looking for suggestions on which model might be appropriate for my case. I have 3 tables that I need to match. Column names don't match but I can modify them. Fields ... do match to some ...
0
votes
0answers
16 views

Marrying classic features with text/chat data

This is an approach to a problem / advice seeking question: I just wanted to get more experienced opinions on how best to combine (in a categorization context) user text/chat entry data and the ...
1
vote
1answer
23 views

Is using unsupervised learning to setup supervised classification reasonable?

I've got a biological dataset describing genes. The overall idea is that there are thousands of these genes to sort through, so if ML can rank them I can then know which should be going into the lab ...
0
votes
1answer
36 views

Suspiciously low False Positive rate with Naive Bayes Classifier?

I am performing phishing URL classification, and I am comparing several ML classifiers on a balanced 2-class data-set (legitimate URL, phishy URL). The ensemble and boosting classifiers such as ...
0
votes
0answers
15 views

Supervised family classificcation with HMM

I have seen that HMM can be use as supervised family classification problem by train one HMM model per each classhttps://stats.stackexchange.com/questions/91290/how-do-i-train-hmms-for-classification. ...
1
vote
1answer
28 views

Using ARIMA parameters when transforming time series to Supervised Learning

When forecasting time series one can change the problem from a classical time series (ARIMA type of models) to supervised learning (by adding lag features). When the time series is long and you ...
0
votes
0answers
3 views

How to implement Association Rules on a different clusters of data points

I have a Hotel Dataset and different attributes are given such as days of booking, last booke, cancelled, charges paid, online/offline booking etc etc. What I want to do is to cluster the data first ...
0
votes
0answers
7 views

Mask R-CNN Model mAP evaluation defaults to same evaluation after multiple training sessions

I am new to computer vision and have been trying to train the Mask R-CNN model on a thermal image dataset. I have about 3k images annotated with different objects such as Windows, Facades, Doors, ...
1
vote
0answers
32 views

supervised learning : approximating a priority function

I am facing the following supervised learning problem: An object is fully characterized by its position in $R^n$. There are $m$ objects. There are fully observable (i.e. their positions are always ...
0
votes
1answer
20 views

How to compare supervised learning algorithm and it's technique ensemble learning algorithm?

I have to compare Support Vector Machine and Random Forest algorithm , but i'm confused how it can be compared, like support vector machine is supervised learning algorithm and random forest is ...
0
votes
0answers
24 views

Measuring performance of classifiers with different/extra classes

Disclosure - This is also on cross-validated, but has no comments or answers. Then I found this forum and thought it may be best suited here. I'm not sure where to post this, or how best to explain, ...
0
votes
0answers
9 views

Supervised dimensionality reduction for multilabel data

re there algorithms for supervised dimensionality reduction like Linear Discriminant Analysis (LDA) for multilabel classification? If I understood it right, the implementation of LDA in scikit-learn ...
0
votes
0answers
19 views

Identify and correct mislabeled categorical data in supervised learning

I have game/player level football data in 230 dimensions and want to classify the likely position that each player was playing in each match. The data is labelled, however each player is classified ...
1
vote
1answer
56 views

How to deal with broad and narrow variance within classes in classification tasks

Let's say I'm doing an animal image classification task (it doesn't have to be image classification - this is just my example), and the training and test data is balanced across classes. The classes ...
1
vote
1answer
38 views

Probabilistic gold standard vs Deterministic gold standard

I understand that we say something as a gold standard when it involves human intervention/judgement/review. But can someone help me understand what's the difference between probabilistic gold ...
1
vote
0answers
13 views

How to update edge features in a graph using a loss function?

Given a directed, edge attributed graph G, where the edge attribute is a probability value, and a particular node N (with binary features f1 and f2) in G, the algorithm that I want to implement is as ...
1
vote
1answer
27 views

DL model to assess quality of image

I have an idea but I am not certain that it can be modeled in a DL architecture. Let's say we have images of different qualities based on color patterns and their assessment as labels in a range from ...
0
votes
1answer
29 views

Multi-Label Loss function and model training

I'm working on Multi-Label problem i.e output can predict 1 or more label as an output and hence training data also have multiple labels. Somehow I'm not able to map such ML model training. Please ...
0
votes
1answer
124 views

Retraining EfficientNet on only 2 classes out of 4

EfficientNet model was trained on ~3500 images for a 4-class classification: A, B, C and Neither – with accuracy of 0.985 – by someone else, not me. I'm quite new to ML. So we have this model, and it ...
2
votes
1answer
21 views

What is the proper way to use time-series data for classification?

I have a time-series dataset for a classification problem. The data contains brain signals collected via EEG eletrodes along 2 seconds in frequency (Hz). The classes are divided in different files (so ...
0
votes
0answers
10 views

What is the general way of encoding multiple features in a supervised HMM for Named entity recognition?

It think that the title of the question is self explaining. I know that if I have an annotated training set (in my case for NER), I can easily extract the parameters of my hmm using the data - for ...
-1
votes
2answers
60 views

Techniques for increase random forest classifier accuracy

I build basic model for random forest for predict a class. below mention code which i used. ...
1
vote
3answers
145 views

How to apply supervised machine learning when the target label depends on multiple input rows?

The problem is a multi-label classification problem. Now, I know how to train and classify using single row with several attributes. For example, if the dataset looks like the first table from the ...
0
votes
0answers
12 views

How to find top N neighbors of a datapoint in a cluster sorted in increasing order of distance from that point?

I am doing a clustering exercise and I am doing it using K-Means. After doing the clustering part, I have a dataframe that looks something like this : ...
2
votes
2answers
176 views

Document similarity

I have close to 50000 documents in plain text format. Is there a way in which I can group similar documents together? Similarity mostly here is the content similarity. Will transforming the text ...
-1
votes
1answer
30 views

Machine learning analysis for data set

I have a data set that contains houses, different features, and its prices. I'm trying to do an advanced analysis for this data set, I already did house price prediction analysis using different ...
1
vote
1answer
29 views

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 ={...
2
votes
0answers
54 views

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 ...
31
votes
8answers
7k views

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 ...
2
votes
1answer
22 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 ...
2
votes
2answers
27 views

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 ...
0
votes
0answers
13 views

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, ...
2
votes
1answer
191 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 ...
3
votes
1answer
30 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 ...
2
votes
1answer
30 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 ...
0
votes
1answer
70 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 ...
0
votes
1answer
25 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 ...
-1
votes
2answers
117 views

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 ...
2
votes
1answer
80 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 ...
0
votes
0answers
23 views

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 ...
0
votes
2answers
50 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 ...

1
2 3 4 5 6