Questions tagged [supervised-learning]
For questions related to supervised learning.
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How to extract features from patterns in time series data
I have a time series welding data I wanted to create a model which can predict some weld parameters but extracting those parameters from time series data is being so difficult.
Currently I tried ...
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Does the order of iteration affect the answer returned by FIND-S?
This paragraph is from the book Machine Learning by Tom M.Mitchell (Page 26):
Initialize $h$ to the most specific hypothesis in $H$
For each positive training instance $x$
$\;\;\;\;\;\;$.For each ...
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Can we generate labels for an unlabelled dataset by doing some feature engineering?
I am very new to ML and currently, I am working on building a model that can predict recurring blood donors (a classification problem). I have a dataset which consists of 25 features (gender, height, ...
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Mechanism of Prediction Readjustment in Supervised Learning and Role of Self-Attention in Sequence Data Relationships
In supervised learning, when the prediction deviates significantly from the expectation, how does it "readjust"?
And... LLMs are a subset of deep learning, just as generative AIs are.
Is the ...
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Any research in "probe-tuning" of LLMs?
Is there any research in "probe-tuning" of LLMs, i.e., tuning LLM's parameter weights such that a specific probe (classifier) is more reliably detecting certain markers throughout the ...
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How can CAPTCHAs be used for both user verification and ML training?
CAPTCHAs (e.g. requiring a site visitor to click all the images of traffic lights in a grid of images) are often used throughout to Internet to verify that a site visitor is a human rather than a bot.
...
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Is validation data needed with generated training data?
I have two systems, a system A that generates some data X and a system B that calculates ...
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Is regression method the best for my case?
newbie here. I'm starting to work on a custom model for a very specific task, so I found no pre-trained models for this task so far.
After checking (un)supervised learning approaches I believe that ...
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How to introduce variation between instances of a neural network?
What are some good ways to introduce variation between instances of a neural network?
I've heard about training each instance on different data, with the same data in a different order, through ...
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How can I transform a signal into another using supervised learning?
I'm trying to transform a signal into another using supervised learning. My main goal is to create a model capable to transform a raw signal (Blue Line) into something similar to the "ideal" ...
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Reinforcement learning with $\gamma=0$ versus supervised framework [duplicate]
I am on a learning phase (still to enter the details but I would like first to get a bird's eye overview). I would like to understand the difference between:
(1) a reinforcement learning framework, ...
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How (if possible at all) the rewards (from the reinforcement learning) can be used to generate the data for the supervised learning?
How (if possible at all) rewards (from reinforcement learning) can be used to generate data for supervised learning? This is very topical question, because human feedback usually comes in the form or ...
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Is there some neural network that implements Least Squares?
I would like to build supervised NN that gets a matrix $A$ and vector $b$ as inputs and returns $x$ as a close result of the Least Squares algorithm for $Ax=b$.
I looked for so works in the field and ...
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How to output a function given a time series data as an input using supervised learning?
I have a spreadsheet with time series data collected from two sensors, one measuring temperature and the other measuring humidity. And I also collected data from an experiment that I conducted, the ...
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How do we determine what is correct and what not in Adaboost
In Adaboost, how is it determined what is correct and what not?
In the following example from StatQuest (in youtube), what correct is
and what incorrect makes sense in real life. But what if we have a ...
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Surveys, Papers, Hand on Tutorials about training data generation for anomaly detection
I am searching for anything related to supervised, semi supervised or unsupervised anomaly detection w.r.t training data generation.
I am looking toward reading any work that tackles the issue how to ...
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How does Supervised learning models handle time-varying data
I need to train a supervised learning model which would take some input which differs in its output relating to time. to better understand my question I would give a simple binary classification, the ...
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Identify features don't hold required information in a ML problem
given a ML model that performs poorly, can you differentiate between those two causes:
bad architecture/not enough data
the features do not hold enough information to solve the problem
I'm ...
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How can I learn to transform one input signal (time series) into another?
I'm posting this question here because I've been trying in vain to solve a problem for weeks and I hope some of you might have some useful suggestions.
Basically, the problem is as follows. I have 7 ...
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How to use information on a function to design a neural network learning that function?
I have a function $g$ that takes a vector $x$ of size $n$ and an integer $k$ in $1, \ldots, n$. I know this function is of the form
$$g(x,k) = G\left(\sum_{i=1}^k f(x_{i})\right),$$ where $f$ and $G$ ...
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Machine Learning Models for Longitudinal Data
Recently, I had the following question about supervised classification models (e.g. random forest) for longitudinal data.
Suppose I have the following data about students passing a fitness test - the ...
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Distinguishing text with opposite meanings in SVM (False Information Detection)
I am currently working on a Binary Text Classification Model (False Information Detection) using Support Vector Machine and used TF-IDF as text vectorizer in Python. I have already tried training the ...
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How can I calculate the parameter $w$ in the third condition of LVQ 2.1 algorithm?
I'm developing a neural network software using several NN architectures including LVQ family. I met a parameter that is used in the 3rd condition of LVQ2 and later versions. It's named $w$ and is used ...
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What's the best way to train data with unbalanced targets?
Suppose I have data I want to use for supervised learning, but there is a pretty bad target/class/labels imbalance. Should I:
Limit the size of the training set to make sure there is a flat target/...
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Is the noise term $\epsilon$ in $y=g(x) + \epsilon$ used to denote the model's imperfection to the real world?
In supervised machine learning, it is common to say that we learn a function of the form
$$y=g(x) + \epsilon.$$
Generally, $\epsilon$ is used to denote noise or, more precisely, any influence by ...
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What problem does the neural network really solve?
In the image below taken from a Youtube video, the author explains that the neural network can be used to fit a relational graph for a set of data points shown by the green line. And that this is ...
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What are some machine learning frameworks for supervised clustering?
I have a task where I need to take "data points" which consist of collections of items. Each item needs to be categorised according to predefined categories. That's the easy part - my ...
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Non-locally Electrically Programmable Logic Gates - Technological Advances Progress
Preface: I’d like to clarify that I understand what a relay is and that a PLC uses a fairly conventional microprocessor that only digitally establishes logical logic gate configuration as a digitally ...
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(explore-exploit + supervised learning ) vs contextual bandits
Lets take an ad recommendation problem for 1 slot. Feedback is click/no click. I can solve this by contextual bandits. But I can also introduce exploration in supervised learning, I learn my model ...
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Extracting keywords from messages
I'm starting a project where I want to extract keywords from given messages. The keywords are for example something like: "hard disk", "watch" or other technical components. I'm ...
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Backpropagation not working as expected
I'm new to neural networks and I try to make a model that is guessing if a point is below or above relative to a function output. The idea is inspired from this video https://youtu.be/DGxIcDjPzac .
...
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580
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How can my CNN produce an "unknown" label?
I have a dataset of 20k images of infected mango. I have built a web-based app using Flask, where a user can upload a picture, and my CNN model detects the disease. I have 6 classes in the model, ...
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How to handle class imbalance when the actual data are that way
My supervised learning training data are obtained from actual data; and in real cases, there's one class that happens less often than other classes, just around 5% of all cases.
To be precise, the ...
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Is this a supervised or reinforcement learning problem, and which algorithm should I use to solve it?
I have a time series data with a little unusual cost/reward function (I haven't seen it before)
The model must predict a $Y$ value for any $X(t)$.
The reward is computed as follows. The model will ...
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Can you correlate decision boundary of final layer of a neural network to predictive distribution?
I was reading in a On the Decision Boundary of Deep Neural Networks
that the final layer of a MLP can be equated to an SVM and can generate decision boundaries similar to methods with SVM. I was ...
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Can we use ML to do anything else other than predicting (in the case of mathematical problems)?
(The math problem here just serves as an example, my question is on this type of problems in general).
Given two Schur polynomials, $s_\mu$, $s_\nu$, we know that we can decompose their product into a ...
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Is there any known approach to generate sets of objects?
I am looking for some known approach, or some previous work, on the following problem:
Let $\Sigma$ be an alphabet of symbols and $\Sigma^*$ be the set of all the strings that you can compose from ...
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Aside from specific training sets, what distinguishes the capabilities of different AI implementations?
(Disclaimer: I don't know much about ML/AI, besides some basic ideas behind it all.)
It seems like ML/AI models can often be boiled down to statistics, where certain levers (weights) get fine-tuned ...
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Literature on the advantages of using an auto-encoder for classification
Given a supervised problem with X, y input pairs, one can do two things for obtaining the function f that maps X with y with Neural Networks (and in general in machine learning):
Deploy directly a ...
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285
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What is the meaning of these equations in Noise2Noise paper?
I am trying to understand what is meant by following equations in the Noise2Noise paper by Nvidia.
What is meant by the equation in this image? What is $\mathbb{E}_y\{y\}$? And how should I try to ...
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Which models can I use for supervised learning with images?
I have to do a project that detects fabric surface errors and I will use machine learning methods to deal with it. I have a dataset that includes around six thousand fabric surface images with the ...
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Is training a CNN object detector on an image containing multiple targets that are not all annotated will teach it to miss targets?
I want to train a convolutional neural network for object detection (say YOLO) to detect faces. Consider this image:
In this training image, I have many people, but only 2 of them are annotated. Is ...
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What is the meaning of "exploration" in reinforcement and supervised learning?
While exploration is an integral part of reinforcement learning (RL), it does not pertain to supervised learning (SL) since the latter is already provided with the data set from the start.
That said, ...
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Multiple Inertia sensors system based for gestures recognition
I am a newbie to Machine Learning field as I am engaging to a personal project that I am trying to use the 6 degree of freedom Inertial Measurement Units(IMUs) measuring the Acceleration acting on 3 ...
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153
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How can we teach a neural net to make arbitrary data associations?
Let's say I have pairs of keys and values of the form $(x_1, y_1), \dots, (x_N, y_N)$. Then I give a neural net a key and a value, $(x_i, y_i)$. For example, $x_i$ could be $4$ and $y_i$ could be $3$, ...
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How to generate labels for self-supervised training?
I've been reading a lot lately about self-supervised learning and I didn't understand very well how to generate the desired label for a given image.
Let's say that I have an image classification task, ...
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43
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Finding whether an input column is missing
I am working on a problem similar to this one:(supervised, artificial data)
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What is a multi channel supervised classifier?
I came across a paper that describes its model architecture in the following way.
Our TRIL network is a two-channel network jointly trained to predict the expert’s action given state and the system’s ...
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Advantages of training Neural Networks based on analytic success criteria
What is the reason to train a Neural Network to estimate a task's success (i.e. robotic grasp planning) using a simulator that is based on analytic grasp quality metrics?
Isn't a perfectly trained NN ...
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How is the reward in reinforcement learning different from the label in supervised learning problems?
How is the notion of immediate reward used in the reinforcement learning different from the notion of a label we find in the supervised learning problems?
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