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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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Is there a consensus on the best model for Antimicrobial Resistance (AMR) prediction?

Some classes of problem are best solved by a specific class of machine learning model, due to the structure of the data (e.g. Deep Learning for computer vision). Prediction of bacterial resistance/...
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29 views

What algorithm to use

I am stuck on what algorithm to use. I want to train my program on a dataset where i have an input image, and an output image which is a modified version of the input. The whole context of the image ...
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Time series data into supervised learning problem Python

I have a data that has a year column, and id column with id's that repeat in different years (id is a categorical variable) and many other columns. I changed this into a classification problem ...
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Modelling a startup's funding journey with Brownian Motion

I am trying to implement a "light" version of a paper (Hunter, Saini & Saman 2017), in which the authors build a model capable of predicting the probability that a startup will exit (either by ...
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1answer
24 views

How does the cost function of LSTM works? [closed]

I am searching to understand how does LSTM network work, but I couldn't find any good sources that explains how it's cost function works? I mean I know we have a sequence of inputs ...
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1answer
61 views

ML regression poor performance

I am experimenting with 3 years time series electrical demand data (kW) for a building and attempting to create regression supervised ML models from sci kit learn regressor algorithms but I have very ...
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1answer
31 views

Unsupervised Learning and Training Data

As far as I know, we need to use training data to find out the relation between the features, also known as input values, and labels, that are output values, in supervised learning. After that, by ...
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26 views

Hyperparameter optimization when calculating learning curves

I'm selecting a model for a regression problem and want to calculate learning curves. My dataset consists of ~20,000 x-y pairs. I'm using kernel ridge regression with different kernels, different ...
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1answer
24 views

Perceptron Learning Rule

I am new to Machine Learning and Data Science. By spending some time online, I was able to understand the perceptron learning rule fairly well. But I am still clueless about how to apply it to a set ...
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1answer
18 views

Supervised or unsupervised learning for predicting energy consumption for new buildings

I’m working on an model for auto dimensioning district heating pipes for new district heating areas (new customers). I have energy consumption data on hourly basis and describe data about these ...
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30 views

How to choose best model checkpoint when training deep learning model on all the data?

When training a final model for production, it's often recommended to train on all available data (train + dev + test), as discussed here. I'm training a deep learning model. I typically save and use ...
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16 views

SVM Cost function change to improve its computational efficiency

While listening to Andrew Ng's course of Machine Learning he said that the SVM's cost function term $\frac{\Theta^T\Theta}{2}$ is usually changed to $\frac{\Theta^TM\Theta}{2}$, where matrix $M$ ...
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Apply Labeled LDA on large data

I'm using a dataset contains about 1.5M document. Each document comes with some keywords describing the topics of this document(Thus multi-labelled). Each document belongs to some authors(not just one ...
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1answer
19 views

Machine learning algorithm to classify matrices [closed]

I want to know what could be first choice for a machine learning algorithm to classify matrices. Each matrix belongs to either class A or class B. The classification problem is: To classify each ...
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1answer
30 views

Similar students using Machine Learning

I have a student performance data, where I have marks of various subjects for the students and I want to find similar students with good marks in a particular subject using machine learning. How do I ...
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17 views

Learn a boolean function

My ploblem is as follows: I have a pool of 32-bit physical addresses. Each address maps to a bank in the DRAM (16 bank in total). I can detect subsets of addresses mapping to the same bank. For ...
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31 views

How should we classify alphanumeric data using supervised machine learning algorithms such as K-neighbors classifier?

My training data set consists of numbers like Q519596, U4414E, EMI3776438, E80700104. I specifically included these 4 numbers from 4 different classes to give the best idea of what you can expect ...
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1answer
23 views

Strategies for continuously assessing and improving model performance

I am building a supervised machine learning model to generate forecast. So I would have historic data like this: SKU, Month, .... other features, Actual Volume ...
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1answer
30 views

Performance of model in production varying greatly from train-test data

I was wondering if anyone has any advice on where to start digging for this problem. I have a model which has gone through development and all train/cv/test data sets now perform above 95% both for ...
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37 views

Adaptive Machine Learning in Python

I would like to build a real time adaptive learning algorithm in Python consuming a data stream. What are some Python libraries that include adaptive machine learning algorithms ? As an example, ...
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Neural Network for detecting/checking for requirements in diagrams

My question is more about what approach is a good/the best approach for my problem: THE PROBLEM - I'm an (mechanical/software) engineer and we take extensive amount of time to review technical ...
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37 views

Improving automated ingestion system using Machine Learning and/or NLP

I'm working on a automated ingestion system which takes a PDF or doc file or a URL. It then parses the file and get me the required text in a json format but there are some error and there are few ...
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Supervised Text Classification (proportions)

Is there any other algorithm (package for R) than the tool kit ReadMe (Hopkins/King) which can give out estimated proportions of categories? The ReadMe software package for R takes as input a set ...
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48 views

What are Supply Chain Management Problem?

Recently when going to data science hackathons, I have found that people mostly ask problem regarding Supply Chain Management problem. Can anybody explain to me what are these problem and how do I ...
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1answer
54 views

Why am I getting crossvalidation scores of 0 only

I am trying Catboost package with iris dataset with following code: ...
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Supervised training based Tagging/Labelling for entities

Let’s say I have training data tagged/labelled like this: ...
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1answer
26 views

Supervised learning for timeseries classification problem

I'm trying to use a supervised classification algorithm on a timeseries problem and my model is performing to well i think. It's a time to failure problem. I have 1000 sensors and have to predict if ...
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1answer
185 views

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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2answers
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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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1answer
51 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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1answer
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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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2answers
62 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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0answers
17 views

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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1answer
63 views

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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1answer
94 views

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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339 views

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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1answer
46 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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1answer
602 views

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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1answer
178 views

how to identify the unknown class in machine learning? [closed]

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
27 views

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
75 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
165 views

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
89 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
55 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
190 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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0answers
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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
110 views

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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107 views

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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24 views

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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0answers
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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 ...