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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11 views

Sampling from deep belief networks

DBNs are generative models, and usually you sample by thermalising the deepest layer (as it's a restricted Boltzmann Machine), and then forward propagating a sample towards the visible layer to get a ...
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ML model for Signal Decomposition

So recently I got a task which can be summarized as follows: Suppose we have 3 functions f1, f2, f3 and a certain combination of the functions gives us ...
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8 views

Does Outliers in Categorical Feature varibales exist?

So, I was working on an Exploratory Data analysis project, after dealing with all the preprocessing of numerical features of the dataset when I started analyzing categorical data(nominal) there I ...
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6 views

Calculate the confidence score (decision_function) of perceptron, by the signed distance of that sample to the hyperplane

I've implemented the binary version of perceptron from scratch, in python. I would like to use it for one vs all classification, by using the one vs all of sklearn. for that, I need to implement the ...
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8 views

How to graph multiple variables

I've been tasked with the challenge of creating ONE singular plot that entails a multitude of relevant given data. There is one dependent variable vs three independent continuous variables, an ...
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Explaining a Conformal Prediction (vs NonConformal)

I'm trying to understand the definition of a conformal prediction and possibly the difference with a non-conformal prediction. What I get as a general idea is that the conformal prediction will be ...
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When does we use weighted LS regression, generalized LS regression, or robust regression in real world?

Recently, I have been reading and studying about the weighted LS, generalized LS, and robust regression. I sort of understand about the theory behind it and how it overcomes the heteroscedasticity, ...
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Suitability of Random survival forest (RSF) as variable selection method for Cox proportional hazard model

I am trying to find ways to validate predictors selected by random survival forest (RSF) for survival analyses. a) Would it be appropriate to use random survival forest as a variable selection ...
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Reporting metrics performance using nested cross-validation with grid search

I have a small dataset with 45 samples in total (25 from class 1 and 20 from class 2) and a large number of features (200). I would like to use nested cross-validation with grid search in order to do ...
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Statistics for Data Science and Machine Learning [closed]

I know there is a lot of topic in the internet regarding statistics, data science, and machine learning. After reading a lot of articles they have a simple explanation about the level of statistics ...
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Price optimization using forecasting with ML

I'm thinking about a good method to do discount/price optimization on the SKU level in an e-commerce store. I have enough historical time series data on sales, daily discounts, product views, etc. and ...
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1answer
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Optimal threshold from a uni-variate continuous variable without target

I have a univariate continuous variable. Now I would like to know is there any objective approach that can give me the optimal threshold that can help me make it a dichotomous variable with values as <...
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Can someone please tell me what's the use of confusion matrix? [duplicate]

I'm new to the data science field, there are two things that I always can't seem to understand. 1)What is confusion matrix and it's application 2)What is the significance of the cross-validation set
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Statistical proof to exclude less frequent records from data during analysis

I am working on reviewing the results of an automated task. For ex, To give you an idea, the data that I have to review looks like as shown below Let's say from the downstream analytics perspective, ...
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1answer
15 views

Best modelling approach with binary outcome and some non-linear relationships, including some “definite 0” regions?

I have 5 predictors and a binary outcome. One of the predictors (X4) is already very informative of the outcome. Basically, for all X4 values that are 0:100, all outcomes are 0. For values 100:150, ...
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1answer
13 views

K means model implementation in python

In my K mean model implementation with K =2, running it 10 times, how to compare clusters with each run to find out which cluster is best? The question says:Write a math expression that would let you ...
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1answer
18 views

Does a threshold effect the training or testing fold in cross validation?

I am trying to better understand how changing a threshold affects a cross validation model. So if you trained a random forest model, the default threshold is ...
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What is the difference between Bayes Error Rate and Irreducible Error?

I can't get the difference between these two kinds of errors. Who can help me?
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How to find similarity in R or Python?

I have a data set as I've shown below: It shows which book is sold by which shop. Also, every book_id has a type. ...
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9 views

SVM and Monte Carlo simulation to compute misclassification error rate

I am trying to solve the following problem with R: use simulation to evaluate (by Monte Carlo) the expected misclassification error rate given a particular generating model. Let yi be equally divided ...
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1answer
18 views

Model selection using nested cross validation

I am working on a school project using remote sensing data, for classification purposes. And I am trying to select the best model (models) for my data. The approach that I adopted is the following: ...
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1answer
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The correct way of performing OneHotEncoding for neural network models

I have a dataset of multiclass (0,1,2) labels. Since I am using Keras, I need to first perform OneHotEncoding on the class column in the dataset using ...
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3answers
533 views

log(1 - softmax(X))? [closed]

Let $\vec X$ be a vector. The $\vec V = \mathrm{logsoftmax}(\vec{X})$ function is defined as: $$v_i = \ln\left(\frac{e^{x_i}}{\sum_i e^{x_i}}\right)$$ This is provided in machine learning numerical ...
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k means in python with BIC [duplicate]

I am new to ML. I am trying to implement k-means which uses a BIC function that takes cluster and data points as arguments and returns BIC value. I need a function to find best k value that is ...
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1answer
35 views

Implementing complex LASSO in Matlab

I want to test LASSO in compressive sensing to reconstruct a sparse signal. I know how LASSO cost function looks like (and I'm fed up with graphs showing different types of norms, I understand exactly ...
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Discrimination vs calibration

So far I have been using logistic regression for binary classification problems usually for unbalanced classes - and would resort to the standard F1 score, AUROC, and Gini to compare and contrast the ...
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spatiotemporal/geophysical forecasting

I am wondering what models to use for geophysical forecasting? I am looking at historical sea surface temperatures over the globe with one datapoint per month, so an input of (lat, lon, # of months) ...
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Get best performing feature

A data set that looks like this ...
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1answer
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Is it possible not to perform transform() on test data

We know that the best practice in data preprocessing (such as standardization, Normalization, ... etc) is that while we perform fit_trasform() on the training data, ...
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2answers
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Logistic Regression gives unexpected results

I am trying to predict binary outcome (Response) with a single feature (V1) using scikit-learn implementation of Logistic Regression (default parameters). ...
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Compare two Image Datasets Distributions for Domain Adaptation - Say MNIST with USPS datasets - Dataset Shift/ Covariance Shift

I am new to statistics, Could you guys help me in solving the below questions: I need to prove that my Image Datasets have Domain Shift/ Covariance Shift/ Dataset Shift. Q-1: What are the ways to ...
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1answer
465 views

Why does ordinary least squares have to be linear in the parameters?

I've been looking into linear regression, and on the wikipedia page it says: "In contrast, non-linear least squares problems generally must be solved by an iterative procedure" This got me thinking ...
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9 views

Kaggle RAM vs Google.collab RAM [closed]

How much RAM is allocated to the Kernel in Kaggle and google.collab ? Which is the best one to use ? Does running a kernel on the web will effect machine RAM too?
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1answer
12 views

How to test if con-infection between microbes is correlated?

I am analyzing the results from a diagnostic test that looks for the presence of micro-organisms in humans. In some cases, there is only one microbe but in others, there are multiple infections. What ...
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1answer
15 views

How to write the correct syntax for this question? [closed]

A dataset named "rain" contains information on raining in four different countries. How to create a subset of the data that only contain raining information when "country" is 1?
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1answer
17 views

understanding 0 kl-divergence loss in beta variational autoencoders

I've been reading this paper "Understanding disentangling in beta-VAE" and there was one part I was confused about. https://arxiv.org/abs/1804.03599 (paper link) On Figure 4, it shows that if the KL-...
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1answer
18 views

Why do we take the ratio of two features?

I've just learned that one technique for feature engineering consist of taking a ratio feature: feature1/feature2 , but I'm quite confused and I have questions: Why does this work ? Is this ...
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1answer
5 views

Why does the BERT NSP head linear layer have two outputs?

Here's the code in question: ...
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14 views

Deriving the basis functions for natural cubic spline

Im looking through Section 5.2.1 of Elements of statistical learning, and am confused by this section I understand that, from this answer , the definition of $d_k(X)$ is important in order to derive ...
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13 views

The gain in Gini index

Consider a dataset with 100 data points with 4 binary attributes each (A,B,C,D).the dataset has a binary class table with 20% of the data points taking value 1 for the label. The rest take value 0. ...
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1answer
21 views

Grid search extrapolation

Hyperparameter optimization via grid search returns a value of a chosen metric for each set of hyperparameters in the grid. Would it make sense to fit the values of the metric (target variable) using ...
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0answers
20 views

Why did logistic regression fail to model non-linear predictors, but cubic splines didnt?

I am reading ESL and was looking at Chapters 4 and 5. In chapter 4 logistic regression is performed on some 'South African Heart Disease Data'. The final model did not accurately model 2 parameters: ...
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14 views

Patient Services Probabilities Prediction

I have a dataset in which I have a patient's diagnosis and service corresponding to those diagnoses. I want to apply machine learning in such a way that. When I enter the patient diagnosis to system ...
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13 views

How to find the similarity?

I have a problem statement but I am not sure how to approach it accurately. Let me explain the statement. Assume that I have a website that many shops are selling books. Some books are very demanded,...
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1answer
40 views

Using the ARI to validate clusters

To validate the results of a clustering solution, I am using the ARI to quantify the agreement with a reference classification method. Something which I do not quite understand is the concept of a "...
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0answers
14 views

Can one predict a variable from a sequence of values?

I recorded the signals from all junctions and motors of a walking robot, which walks using the input from different reinforcement learning models. Now I would like to find a way to differentiate ...
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6 views

Does spread in error reflect spread in coefficient values when coefficients are dimensional and have different units?

I have two very different empirical models that estimate a quantity $Z$ from two quantities ($x$ and $y$). Lets call the two models (highly non linear) $F_1$ and $F_2$ $$ Z = a_1F_1(x,y)$$ $$ Z = ...
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Variance, std and mean in Anomaly Detection [closed]

As a first step of a project regarding anomaly detection, I have written a short program that goes through my dataset and gives an output CSV file consisting of 4 columns: Name of the string Mean on ...
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0answers
10 views

How to plot profile of log likelyhood function from r code? Please metation the r code [closed]

I want to introduce in probability model. I have calculate the value of MLE. problem in log l
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8 views

Statistically test differences of model performance on two different datasets

Suppose I have an SVM and a NB classifier that try to predict ownership of a particular text. For each of the algorithms, I train a model on 10 disjoint sets of training data. Then, I test them on ...

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