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.

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How are bias and variance related to overfitting and model capacity?

Many people use the MSE decomposition to illustrate bias and variance. However, is there any statistical learning theory connecting these concepts? Namely, is there a formula calculating model ...
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How to differentiate the hinge loss?

I'm asked to differentiate the following hinge loss term. $$ \dfrac{1}{n}\sum _{\left( x_{i},y_{1}\right) \in S}\sum _{j'=1}L\left( w^{j'};\left( x_{i},y_{i}\right) \right) $$ where $$ L\left( w^{j'};\...
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How to formulate a machine learning problem?

Virtually no books talk about how to formulate a ML problem, especially the process of creating the right label. Here I use an online hotel search portal as an example to explain my thought process ...
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About the FC layer in a CNN

So we know that the major disadvantage of pushing images through an ANN is due to the loss of information, particularly spatial information. But in regards to CNNs, in the last layer of the ...
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Getting trip information from AVL data

I got a problem which needed to solved using Machine learning. The problem title is "how to generate trip information based on AVL". The dataset generated from AVL device is collected by ...
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1answer
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Market Mix Modeling using Random Forest

I am trying to build a random forest-based market mix model, wherein I want to calculate the contribution of each of my X variables towards the target. Typical MMM problem statement, but here am not ...
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Time series prediction completely off using ESN

I am attempting to predict closing prices based on closing prices extracted from OHLC data from a two-month window with 10 minute intervals (roughly 8600 data points). For this attempt, I am building ...
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How to prove that a function is 2-increasing (copula)

There are three conditions to prove that a function is a copula: $C(u,0)=0=C(0,v)$ grounded. $C(u,1)= u, C(1,v)= v$. $C(u,v)$ 2-increasing function. Here I am concerning in the last condition how to ...
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Uplift modeling for Train, validation, test data sets

I am wondering when I should tune hyper parameter when we build uplift model. In a normal machine learning context, data will be split into train, validation, test. And, we train the model with train ...
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Is there any appropriate technique to look for a continuous, representative part of a time series dataset?

I would like to know if there is any machine learning technique that could be used to solve the problem as follows. Imagine a time series dataset with several rows (observations) and many columns (...
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Why does my model produce unrealistic output?

I am trying to run a binary classification problem on people with diabetes and non-diabetes. For labeling my datasets, I followed a simple rule. If a person has T2DM...
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1answer
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How to test significance of two ROC with MLeval

I've two ROC derived from caret and I'd like to test if the relative curves are statistically different: ...
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Which machine learning model? For small dataset and very long feature vectors

I've got two questions about which model might be the best for the assumption described below: In the assumption, we are given various of compounds, wanting to determine the result of the reaction of ...
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From k-NN density estimation to classification, two different approachs

One way to derive the k-NN decision rule based on the k-NN density estimation goes as follows: given $k$ the number of neighbors, $k_i$ the number of neighbors of class $i$ in the bucket, $N$ the ...
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What does it mean to have 'R^2 larger than chance' (from sklearn docs)

See the following: From : https://scikit-learn.org/stable/modules/permutation_importance.html The part I'm unsure about is: Its validation performance, measured via the score, is significantly ...
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What are the differences between Linear Regression in Machine Learning and Linear Regression in Statistics?

I am wondering what the differences are for linear regression in a machine learning context versus a statistical context. Are there any conditions that are assumed and need to be checked in statistics ...
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Interpolation using Gaussian processes

This is about Gaussian process interpolations, where the given data are f(0) = 1, f(0.4) = 3 and f(1) = 2. Assume that the covariance function used is the exponential covariance, where the expectation ...
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Bootstrapping GAM LOESS models with Multiple Predictors [closed]

I have a data set with multiple predictors and am using a GAM model in conjunction with LOESS. I am trying to replicate this but include the bootstrap process as well. The following code is the ...
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How to decide whether to use regression or classification model?

I just started machine learning , and I was confused about which model to use, regression or classification , when we have a target variable like age or a variable like movie rating , which may have ...
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Estimators that relate model accuracy to data distributions

Consider a set of dependent variables $D$, set of independent variables $I$ and $O_1, O_2,\ldots,O_N$ observations of these variables. The dataset is short and wide, $|D| = 3*N$. For each $j \in I$, ...
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Logistic regression on all subsets does not work well

I have approximately 3k data rows. I wanted to get a model which can says whether a row should be labeled A or B. I've used logistic regression and trained model for all subsets of features that I ...
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Hypothesis tests in Machine Learning: Independence assumption violated?

Assuming I have a training set that is used to train 3 different random forest models. The values of the response variable $y$ are the same for all of the 3 models. But the predictors $x$ differ ...
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How to control for Co-variate shift in test data set compared to train data for regression task?

I am working on a regression project. But I am facing the problem of covariate shift in features due to time delay.Test data was collected a year later due to which there has been some change in ...
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improve detect filter microphone deepspeech [closed]

We saw an error when we connected the microphone to the neural network in deepspeech https://github.com/mozilla/DeepSpeech For example, the user says Hi And software in the output H Typing. What ...
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1answer
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Statistical Learning. Contradictions?

Currently I am re-reading some chapters of: An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (Springer, 2015). Now, I ...
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1answer
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Likelihood Ratio Test vs. wald Test for P-values

I fit a logistic regression model with 14 predictors, here's the code and output: ...
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On solving ode/pde with Neural Networks

Recently, I watched this video on YouTube on the solution of ode/pde with neural network and it motivated me to write a short code in Keras. Also, I believe the video is referencing this paper found ...
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Any help with this statistic question is much appreciated! [closed]

I am having a little help with this stats question. Any help with this is much appreciated!!
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How to understand what linear transformations are doing when estimating a regression?

I am trying to better understand, ideally in English, what exactly a linear transformation is doing when we compute something like OLS (but the process holds for basically every statistical model). We ...
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Build a custom grid search [closed]

I need to build a grid search for tuning hyperparameters. Supose a two ranges: lambda = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1] and ...
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Linear Regression when we have mix of variables

I have a regression problem where predictors are mix of integers and probability values. The dependent variable is in $[0,1]$. For example, ...
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Why is it said that pasting using sampling without replacement?

Breiman (author of pasting) in his article written about two kinds of pasting: Rvote and Ivote. Why this and lots of other sites I can read that "When sampling is performed without replacement, ...
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unsupervised anomaly detection on sparse data

Given that I have a very sparse data matrix with continuous features, like this dataframe for example ...
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How to create one hot segmentation masks from rgb mask image for multiclass segmentation?

I am trying to train Deeplabv3 for semantic segmentation on BDD100k dataset. It contains 20 classes for segmentation task. In the Dataset labels are provided as RGB mask image (3 channels). How do I ...
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Question about Dimentional Reduction [closed]

Consider the vectoryi= (yi1,...,yip)′, whose sample mean is ̄y=0, andsample variance-covariance matrix isS. Denote the first principal componentofyas ̃ci= ̃w′yi with corresponding eigenvalue ̃λ &...
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Random forest classification: difference between feature importance vs feature selection

I'm getting confused about the steps in RandomForest(RF) model building, speficially in terms of feature importance and feature selection. From my shallow knowledge, any machine learning building will ...
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Which SVM kernel (or classifier) to use when there is a structured covariance among the features?

I am trying to use SVM for multi-class classification. The input features are assumed to be generated from a multi-variate Gaussian distribution. Each class corresponds to a different set of mean ...
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1answer
80 views

Bayes theorem in advertising [closed]

I am new to Bayes theorem, and was wondering if anyone can guide me through this question. An advertising agency want to analyze the advertisements for a product. They want to target people from all ...
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How many points needed to compute the Homography? [migrated]

I'm working on a project where i'm using planar homography. As seen in the above image, every point gives two equations and since the homography matrix has 8 degree of freedom, 4 points are enough to ...
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What is the difference between F1 F1 Macro and F1 Micro in python's TPOT? As well as Recall, Recall Macro and Recall Micro? [closed]

These are scoring specifications to run TPOT. The parameters options for the TPOTClassifier function are the following: 'f1', 'f1_macro', 'f1_micro','recall', 'recall_macro', 'recall_micro'. https://...
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Extrapolation of COVID cases based on textual analysis (ML)

I am just learning about machine learning and have strong interests in learning about how textual analysis from machine learning can be applied to time series prediction. A few examples I thought of ...
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Range of values for hyperparameters of the KNN

Algorithm : Classification by k-nearest neighbors with Euclidean distance (neighbors.KNeighborsClassifier). Determine the important hyperparameters (2 maximum) that can significantly influence ...
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Correlated random variables and ensembles (law of large numbers?)

Consider $n$ i.i.d random variables. By the law of large numbers (LLN) the sample average would converge after some time to the expected value. Let's assume the random variables are correlated. Would ...
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What is the way to compare SVM output?

How can I rigorously compare the results from SVM? I have a feature matrix that contains ~1000 features and the label is either 1 or 0. The features can be grouped into 4 categories, let's say they ...
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1answer
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How does one sample all images uniformly when the data set is organized in hierarchies?

I have a data set with $C=64$ classes and $N_c = 600$ images and total images $N = \sum_c N_c$. Each class has a separate folder for each class. I want to be able to sample images as if they were in a ...
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Understanding the advantage of formulating $y=ax+b$ in $y=ax$?

Firstly I would like to point out that this is the question extended from the original question posed by Abhinav Gupta in the link Understanding linear projection ...
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NLP technique for multiple sentence fusion (combination) into one readable sentence

looking for help in knowing if there is a possible solution in natural language processing that could help me use or build a model that combine two or more different sentences into one for example: ...
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1answer
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Multi-regression model validation

I'm a new-bee in the ML modelling and have created a multi-linear regression model. I have got the rmse score for the model as approximately 5. How am I suppose to interpret this?
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1answer
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What does vanishing gradient problem exactly mean? [duplicate]

I'm currently doing some stuff with ML, and I created a LSTM model to recognize activities such as walking or running. I have read that LSTM has advantages over traditional RNNs due to addressing the ...
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How can I calculate the subgradient of this function?

I am new to the concept of subgradient and am struggling hard while trying to calculate the sub-gradient of Absolute Loss Function with absolute regularization $f(\theta) = \sum_{k = 1}^M | y_k - \...

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