Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

0
votes
0answers
24 views

Python: How to find the value that separates 2 different clusters?

I am applying an unsupervised learning algorithm for building an anomaly detection using OneClass SVM method and then plotted it to visualize how it looks. I got 2 clusters: one red and the other ...
0
votes
0answers
31 views

Predicting future price in high inflation economies

I am trying to create a machine learning model in a country which has high inflation. With this model, I am trying to predict the price of a second hand car. As my train data, I have second hand car ...
-1
votes
1answer
18 views

increase dimensionality svm example

I understood that increasing the dimensionality in SVM will help, but I try to understand the concept mathematically, as described in Breiman, Leo. "Statistical modeling: The two cultures." ...
0
votes
0answers
19 views
1
vote
0answers
16 views

How to use Machine Learning to discover important biomarkers in an unbalanced small data set

I have a project which I am just starting out, I am only just learning machine learning and statistics so I am somewhat unsure as to what approaches will be good to start off with, and I am sorry if ...
0
votes
0answers
11 views

How do I analyze time series with less variation in values?

I know i am asking a very generic question but this is something that i encountered in one of my projects. I am working on churn prediction for a bank and one of the features that i was using average ...
0
votes
0answers
31 views

Data splitting if there is 'block' missing data?

We may have data from different data sources. Some samples can get data from every possible data source. But others can only obtain information from one source. Each source may contain hundreds of ...
0
votes
0answers
16 views

Clustering/Similarity between drivers

I have a dataset that contains initial and ending points of car trips: ...
0
votes
0answers
7 views

classify according to one variable and no classes

I have a problem, I think that is common but I don´t have idea about how to proceed. I am looking an elegant solution for it. I have N groups and two variables for each group. After that I have ...
-1
votes
0answers
23 views

what is the parameterized policy for Example 13.1 Short corridor with switched actions?

in Sutton's book Reinforcement Learning: An Introduction (http://incompleteideas.net/book/bookdraft2017nov5.pdf) Chapter 13. for Example 13.1 Short corridor with switched actions, for calculating the ...
0
votes
0answers
11 views

Models for identifying anomalies in process data

We have a manufacturing production line with sensors collecting material weights at different locations along the line. The data structure looks like something below: We have noticed instances that ...
0
votes
0answers
11 views

oversampling data with subclass

Oversampling of under-represented data is a way to combat class imbalance. For example, if we have a training data set with 100 data points of class A and 1000 data points of class B, we can over ...
1
vote
0answers
18 views

How to find a transformation of a random process X to make it distributed as a reference process Y?

I am thinking how to use GAN or KL Divergence as a loss function to enforce specific specific distribution on the feature space: Let $X \sim D$ where $D$ is some distribution. Assume we know a ...
0
votes
1answer
27 views

On starting feature engineering

I would like to start my feature engineering process by first selecting a subset of features that are highly correlated with the target feature. However, if I do select let’s say the top k in terms ...
0
votes
1answer
11 views

Correlation Analysis and Data Leakage

In machine learning, we perform feature engineering and selections in pipelines and crossvalidate to obtain results in order to avoid data leakage and avoid introducing prior knowledge into the ...
0
votes
0answers
4 views

kernel regression for extensive system?

I was reading this post on Reddit here thinking about building a predictive model for an extensive system. I know it is widely known that a neural network might be a better choice to apply the ...
1
vote
2answers
73 views

How to explain the utility of binomial logistic regression when the predictors are purely categorical

The resources that I have seen feature graphs such as the following This is fine if the predictor $x$ is continuous, but if the predictor is categorical and just has a few levels it's not clear to ...
2
votes
0answers
16 views

Binary Classification for Customer Dataset without Customer ID

My dataset is a log of phone calls. Each row represents a customer interaction with attributes such as customer age, customer job, and interaction outcome ('buy' vs 'no buy'). EDIT: the interaction ...
0
votes
1answer
17 views

Using a larger validation data set reduces the chances to select an overfitted model

Does a larger validation data set reduce the chances to select an overfitted model?
0
votes
0answers
11 views

Feature Selection in Machine Learning [duplicate]

Is it appropriate to conduct feature selection (e.g., Recursive Feature Selection) on a data set IN ADVANCE of model fitting to scale down features for more expedient machine learning model fitting? ...
0
votes
2answers
27 views

Sampling Big Data for Machine Learning [closed]

In practice, how does one go about sampling a from big data set (eg. +/- 50 million distinct observations) to perform ML using Python? Most non-parametric models (e.g., SVM, ensemble models) start to ...
3
votes
1answer
222 views

Does regularization penalize models that are simpler than needed?

Yes, regularization penalizes models that are more complex than needed. But does it also penalize models that are simpler than needed?
0
votes
0answers
17 views

Using Synthetic Data Based on Real Data for Classification

The goal is to classify three different cell types based on certain features (e.g. area, shape tensor etc.). However the amount of labelled training data I have is very small. Therefore, it was ...
2
votes
1answer
29 views

Sum of Squared Error Chi-Square distribution degree of freedom in Multilinear Regression

In this link it says that $Y$ variables has zero covariance (because covariance matrix has only diagonal terms) which implies they are independent. Actually in linear regression $Y$ takes its ...
0
votes
0answers
10 views

Chi-square test on regression model

I have a regression model to build, with data having few categorical variables and my target variable is continuous. I wish to implement chi-square test for feature selection of categorical variables ...
1
vote
1answer
18 views

Model Deployment: export Scikit Learn Pipeline or Model only?

Following ML best practices, I use Scikit Pipelines to make sure my data preprocessing is the same at each model development iteration. Also as a best practice, once I have completed model ...
0
votes
2answers
30 views

Taking constant out of multivariate normal

For a univariate normal distribution $X \sim N(0, k\sigma^2)$ we can take out the $k$ to get $\sqrt{k}X \sim N(0, \sigma^2)$. In the multivariate normal case is there something similar? If $\textbf{Y} ...
2
votes
2answers
73 views

Difference between a mixture model and ensembling

Can someone explain to me the difference between a mixture model and a model ensemble? It seems both of them incorporate multiple models.
1
vote
0answers
23 views

Effect of class imbalance on logistic regression (mathematical basis)

A number of posts, and papers, state that logistic regression (LR) is robust in the face of class imbalance. Unless the imbalance is extreme (e.g., events=0.01 or less), with adequate sample sizes ...
1
vote
1answer
34 views

What type of neural network is used for image style transfer?

Tell me, please how to train a neural network to redraw pictures of people under the style of artists? For example Leonardo DiCaprio as Vincent van Gogh's Self-Portrait. I want to understand: What ...
3
votes
0answers
50 views

Decomposing R^2 into independent variables

Consider a linear regression model: $$y = β_0 + β_1X_1 + β_2X_2 + ... + β_kX_k + ε$$ where $R^2 = 1 - (SSR/SST)$. I would like to determine the contribution of a factor $i$ (call it $R^2_i$) into ...
0
votes
0answers
12 views

Set similarity as weight to ratings

I have a problem deciding which similarity function to use. I want to find the similarity between the users based on their requirements about computer performance metrics normalized to 1. Each user ...
1
vote
1answer
28 views

how Deriving the formula for “The on-policy distribution in episodic tasks”?

in Sutton's book Reinforcement Learning: An Introduction Chapter 9, how to drive the formula for "The on-policy distribution in episodic tasks" as flow? that h(s) denotes the probability that an ...
1
vote
0answers
35 views

Predicted Ys for Lasso regression show negative correlation with observed Ys

I observed than when using Lasso regression and KFold crossvalidation with my data, predicted values show negative correlation with observed values. I tried to replicate the problem with a randomly ...
3
votes
2answers
52 views

Adaboost Notation Confusion

The adaboost algorithm is as follows: $\mathbf{Input}$: sequence of m examples $<(x_1,y_1),...,(x_m,y_m)>$ with the labels $y_i \in Y = \{1,...,k\}$ weak learning algorithm WeakLearn ...
0
votes
0answers
10 views

What would be the “Leo Breiman style” alternative to Platt scaling?

In Platt scaling[1], you fit a function to the predicted raw scores from a trained model, on a test set, in order to convert future scores into probabilities. The function is: p(x) = 1 / (1 + exp(a*x ...
0
votes
0answers
21 views

Finding similarity dissimilarity between different groups of vectors

Suppose I need to combine or group together set of vectors in one area and another group in other areas, however I need to place these groups in a plot so they are scattered in the screen per ...
0
votes
0answers
11 views

Package to perform 2nd degree polynomial regression with L1 penalty for use of the 2nd degree

I'm trying to fit either a straight line or 2nd degree polynomial through many sets of points (2-dimensional data). I would much prefer a straight line over a polynomial, so am trying to penalize the ...
0
votes
1answer
27 views

Get lower bounds and upper bounds of a curve

I have fit the wave data as below using Least Square optimization and used Root Mean square to calculate upper and lower bounds. I wanted to know is there any other alternative exists which gives a ...
0
votes
2answers
18 views

Problems with sampling with replacement for generating train, test, and validation data sets

When creating train, test, and validation data sets for machine learning, random sampling without replacement is done to create disjoint data set partitions. Is there anything wrong with using random ...
0
votes
1answer
9 views

How do I run cross validation on a decision tree in an uplift model?

I have this model from the uplift package, ...
1
vote
0answers
10 views

What measures of an ML algorithm's 'accuracy' are mostly consistent as the number of classes to predict into varies?

For a research project, I've got a bunch (N=507) of 20-second VR tracking data clips (6DOF x head and hands), each from a different participant. My goal is to predict the participant using a small ...
1
vote
1answer
19 views

How do I code interaction terms when I have dummy variables?

I have a dataset from an AB test. It shows the conversion rate per treatment group and the categories within each variant. ...
0
votes
0answers
22 views

Audio files and their corresponding spectrograms for image classification process

Suppose I have a dataset of audio files that I have to use for whale sound classification. I am choosing the strategy of treating it as an image classification problem by using their corresponding ...
0
votes
1answer
34 views

Pre-Processing audio data for whale sound classification using CNN

Previous researchers have used techniques like Denoising using Spectral Subtraction method and calculating Short Time Fourier Transform (STFT) by dividing the audio data into fixed size chunks and ...
0
votes
0answers
42 views

Why do the posterior probabilities violate the axioms of probability when we apply Bayesian update without likelihood computation?

Suppose that the unknown parameter $\Theta$ is Bernoulli and we make $n$ observations $X_1,X_2,\ldots,X_n$, which are continuous random variables. Assuming that $X_1,X_2,\ldots,X_n$ are conditionally ...
0
votes
0answers
14 views

Row aggregation of multiple records

We have a syslog dataset with different Timestamps and 3 other features pertaining to syslog information such as Process, Trace information, SeverityType etc. Below is the dataset format with ...
0
votes
1answer
21 views

Kolmogorov Distribution D statistics

As far as I have searched the cumulative distribution function of 𝐾, asymptotically (kolmogorov distribution) is given by Pr(𝐾≤𝑥)=1−2∑∞𝑘=1(−1)𝑘−1𝑒−2𝑘2𝑥2=2𝜋√𝑥∑∞𝑘=1𝑒−(2𝑘−1)2𝜋2/(8𝑥2). But ...
1
vote
2answers
42 views

Multi-View Survival Analysis

I have a data set containing various subsets of medical data about a cohort of patients. For example there are blood test results, demographics, medical examination results and a medical history among ...
0
votes
1answer
30 views

Predicting an interval by deep learning or other machine learning methods

I have a distribution built on an interval for example [v_min, v_max], given a good estimate on the interval, the performance of the model can be good. If the ...