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# 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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43 views

### Can least-squares linear regression ever produce no solution at all?

Is it ever possible for least-squares linear regression (linear in both features and weights) NOT to produce a solution? That is, after we set each partial derivative to zero, can the resulting system ...
268 views

### Binary classification using GPML toolbox;

Using the demo given in the demo_classification file, I am trying to do a binary classification where each of my class contains 10 samples of 73 dimensions. Following is the code where I try to '...
4 views

### difference between RBF kernel ridge and gaussian kernel regression

This may seem a very naif question: theory frameworks behind kernel ridge regression and classic, non-parametric, kernel regression are very different, but still, from a practical point of view, I can'...
21 views

### Help understanding Vanishing and Exploding Gradients

I am following deeplearning.ai's videos on Coursera. I have a couple of questions regarding vanishing and exploding gradients. The following is Prof Andrew Ngs lecture slides: From what Prof Ng says ...
32 views
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### How XGBoost use Histogram to Determine Splitting Features?

I'm trying for some time to understanding, the splitting method used in XGBoost to determine the best split. But unfortunately I didn't find any clear explanation of it. I found this post which ...
128 views

### Random variables $X, Y$ such that $X$, $Y$ and $\sqrt{X + \sqrt{Y}}$ belongs to the same family of distributions?

Is there a family of positive distributions such that if $X$ has the distribution in question, then $\sqrt{X}$ also has a distribution from the same family. Ideally, it would be great if $X+Y$ also ...
35 views

### Does Bias-Variance Tradeoff always exist?

I'm following deeplearning.ai's videos on Coursera. In one of the videos, Prof Ng mentions: So a couple of points to notice. First is that, depending on whether you have high bias or high variance, ...
433 views

### What algorithm should I use to predict a continuous dependent variable from multiple continuous & categorical independent variables?

I'm software engineer of an E-commerce company, facing a problem like this: An e-commerce shop sells their products daily and wants to know what conditions that might improve their sales. I'm ...
247 views

### Estimating conditional probability with many samples

I am confused about the estimation of conditional probabilities. Suppose I want to predict a binary outcome variable $Y = 0,1$ given $n$ categorical features $X = (X_1, \ldots, X_n)$, i.e. to ...
273 views

### When doing Cox regression, what should we take as event duration for censored data, and how should we divide the data into training and testing sets?

I am starting out with survival analysis, and am confused about some things specifically in Cox regression. I have not found a tutorial that explains these things clearly, that's why I'm posting this ...
6k views

### What is “baseline” in precision recall curve

I'm trying to understand precision recall curve, I understand what precision and recall are but the thing I don't understand is the "baseline" value. I was reading this link https://classeval....
136 views

### Independent and dependent variables Machine Learning

I want to start a regression model on lottery numbers, my database consist of the dates, and results(numbers). In order to do a regression model I believe you need independent and dependent variables, ...
8 views

### Why is the stochastic gradient of a layer almost orthogonal to its weight?

In the paper Fixup Initialization: Residual Learning Without Normalization. In Page 5 when talking about effects of multipliers, the authors mentioned that Speciﬁcally, as the stochastic gradient ...
126 views

### Score of importance from feature selection techniques

Can I get the score of importance for each feature in feature selection methos such as Chi2, Information Gain (IG), or Recursive Feature Elimination (RFE)? Or they just provide a list of important ...
272 views

### Is it possible for a reinforcement learning agent to create or generate additional features

Based on what I've read, the best model-free reinforcement learning algorithm to this date is Q-Learning, where each state, action pair in the agent's world is given a Q-value, and at each state the ...
509 views

### Extending the idea of Bootstrapping to Train Test splits of a Dataset used to learn a Classifier in Machine Learning

In Machine Learning the standard practice for learning a Classifier --e.g. fitting a Logistic Regression model-- and then validating its performance is to split the original/available Dataset into a ...
21 views

### What is the intuition behind pi in the PDF of a Normal Distribution ? Is it related to some sort to a circle / sphere

The PDF of a Normal distribution is given as below I am aware of the various properties of Normal distribution and how the two parameters mu and sigma affect the shape of the distribution. What is ...
14 views

### Classifier output has 3 distinct peaks. Why? [on hold]

I trained a classifier on this dataset from r/ChangeMyView (https://chenhaot.com/pages/changemyview.html) on individual comments to predict whether or not that ...
92 views

### RBF kernel mapping

I was reading that the Gaussian/RBF kernel maps its input onto the surface of normalized hypersphere. Our RBF kernel given by: $k(x,z) = exp(\frac{- ||x-z||^2}{2\sigma^2})$ Can anyone explain why ...
8 views

### Oversampling methods for numerical data (regression)

There are many oversampling methods for categorical labels (for example SMOTE and Rose, etc.). But, are there oversampling method for numerical labels (the thing that I want to predict with my ...
46 views

### How can I get the optimal perturbation of a trained model?

I get stuck while reading Goodfellow's paper on adversarial networks. In the explanation of the Figure 2 he stated that: b) The sign of the weights of a logistic regression model trained on ...
22 views

### About the need of splitting data in stacking

I learned stacking of machine learning in a book, hands-on machine learning 2nd edition (2019). The picture was cited from hands-on machine learning 2nd edition (2019). In the above situation, ...
26 views

### How is Akaike Information Criterion related to Information theory?

How is the Akaike Information Criterion (AIC) related to Information theory ? I mean from the equation (below), it is not at all intuitive how information theory comes into picture. Also is AIC ...
220 views

### Best apparoaches for feature selection in multilabel classification

I have dataset which consists of around 46k observations and 20k features. The target vector is of length 75 (and so the target matrix is 46k x 75). among the features few are categorical and others ...
24 views

9 views

### Hard classification problem - test set accuracy seems to cap out at a certain value regardless of architecture [duplicate]

I've been working on a hard binary classification problem (50-50 split between classes). I've tried a variety of different network architectures and training schemes - dropout, no dropout, batch ...
6 views

### How to reshape input data in RNN model for prediction [on hold]

While making prediction with a built model using new data, an error returned because the shape is different: Here's the code: ...
30 views

### Matching vs simple regression for causal inference?

This is a really simple, newbie question. I am really confused about the notion of matching and when it can be used instead of a multiple regression? Assume I have listed all the confounding ...
11 views

### Including ratios as features in machine learning algorithms [duplicate]

Assume that body mass index (BMI) is a good predictor for early death which we are trying to model using a host of different algorithms. A colleague posed the following to me: would it be better to ...
14 views

### Land Method for Lognormal Distribution

The Land Method is explain here. Anyone knows how I can look up the H*1-α* It says "Tables of these values are given by Gilbert (1987, Tables A-10 and A-12) and Land (1975). " Gilbert (1987) is not ...
21 views

### Is term “metric” for evaluating machine learning model misnomer?

Term "metric" is used in many popular machine learning articles [1, 2] for describing an evaluation criterium of the performance of a model. Although, mathematically is the term defined as: In ...
8 views

### Feature Extraction, Moving window approach [on hold]

I am new to the ML and I only have the strongest will power to learn it. Question: I have the time series data and I want to approach the ML algorithm by extracting features, I didn't choose the ...
9 views

### Product/SKU level time series forecasting [on hold]

Predict demand of product at each outlet for next 6 months 5 – 7 years of sales data at outlet level for each and every brand is available As it is a time series problem we need to design per outlet ...