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7 votes
2 answers
483 views

Pearson correlation as a metric for the quality of regression models

A paper I saw used the Pearson correlation together with MSE to measure the performance of a machine learning model. After doing some research, I have seen that using Pearson correlations to evaluate ...
Degers's user avatar
  • 93
7 votes
4 answers
835 views

Why are statistics textbook questions so frequently totally artificial?

Anyone who reads the questions here on a regular basis quickly recognizes some questions as being from textbooks or exams. Such questions need the self-study tag and one reason for closing a question ...
0 votes
0 answers
13 views

Is it okay to report zero eigen values for some PC components if the first few components are greater than one?

I have a dataset which collected household responses over 3 years. It is unbalanced since not all households participated during the three surveys. I run multilevel PCA in stata to account for within ...
Zainab Hassan's user avatar
1 vote
0 answers
22 views

Weighing hypotheses after seeing the data vs. Consistent learning

In the chapter about nonuniform learning in the book "Understanding Machine Learning, S. Ben David et al." (its free online version here), the authors wrote: if we commit to any hypothesis ...
Tran Khanh's user avatar
0 votes
0 answers
11 views

Why is the estimation error smaller in Structural Risk Minimization

On p.87 in this online Understanding Machine Learning book, the authors wrote: Unlike the ERM paradigm discussed in previous chapters, we no longer just care about the empirical risk, $L_S(h)$, but ...
Tran Khanh's user avatar
0 votes
0 answers
16 views

Is there something wrong with my learning curve or my model because it starts at the end of tail completely opposite?

Hello, Would be nice if you could review my graph and tell me if there is something wrong or not. The context is that it uses a MLP.
Kelvin Li's user avatar
0 votes
0 answers
19 views

Can this feature be used as input to cnn based on the q-q plot?

I have normalised my input features and target variable using the quantile transform by sklearn. The Q-Q plot of one of the feature after normalisation is given as below. Is this feature normalised? ...
Sara's user avatar
  • 1
1 vote
2 answers
195 views

Bayesian Learning: Finding the variance of noise

Suppose $x_i \sim N(10,4)$ - ie, the distribution is known. There is a noisy signal $s_i \sim N(x_i, \sigma_e^2)$ and I want to estimate $\sigma_e$. I see some pairs ($s_i, x_i$) but they are not '...
user20380762's user avatar
1 vote
1 answer
40 views

Why does the performance on the training set go down as the number of samples increases?

To my knowledge there are two types of learning curves, those that show the progression of the performance as the amount of epochs progresses, and those that show the performance progression as the ...
Valo's user avatar
  • 43
0 votes
1 answer
85 views

Python Machine Learning Prediction Model - Predict String Variable based on multiple other string variables

I'm very new to Machine Learning, so please forgive the simplicity here. It's probably because I'm new to this, but I can't seem to find anything relevant enough online to help here. I have data on ...
user2066464's user avatar
0 votes
0 answers
23 views

How does sample size selection happen which is generally used as $20\times (p+q)$?

Can anyone explain me about how sample size selection happens which is generally used as $20\times (p+q)$? Here $p$ is the number of parameters in the final model and $q $ is the number of parameters ...
Ishanee Mahapatra's user avatar
2 votes
1 answer
111 views

Application of Classical Multidimensional Scaling in Matlab on new data

I would be happy if someone gives me a hint for two following questions in Machine Learning - related application of Classical Multidimensional Scaling in Matlab: 1.) It is recommended (but in my ...
De Ro's user avatar
  • 21
2 votes
1 answer
62 views

Model suggestion alternative to categorical regression

I am developing a model framework in the context of online marketing: the dependent variable is purchase, the independent variables includes a mix of continuous (e.g., impressions, ad spend) and ...
yao's user avatar
  • 23
1 vote
0 answers
33 views

Which ML method should I use to make a prediction function for accident data?

I have road accident data from 2000 to 2020 with counts divided into categories like "Junction Type" etc.? I want to build a prediction model using ML, So which technique should I use Linear ...
PIYUSH JAANGID's user avatar
0 votes
0 answers
35 views

Learning operating probabilities from interval data

Suppose I have a machine. When the machine is active (operating), it runs for at least $\mu > 0$ time. I know that at some point in the time interval $[l, h]$ ($l, h \in \mathbb R_{\ge 0}, l < h$...
Nelewout's user avatar
  • 158
1 vote
1 answer
738 views

Reduce or Increase Dimensionality? Machine Learning

I had a question about machine learning and dimensionality. In many machine learning methods, we try to reduce the dimensionality and find a latent space / manifold in which the data can be ...
DXinhua's user avatar
  • 13
1 vote
1 answer
64 views

Limit of Momentum Update Equation

I am self-studying on optimization algorithm on https://d2l.ai/chapter_optimization/momentum.html and couldn't get my head around some derivation: Instead of the standard gradient descent update ...
WeiShan Ng's user avatar
2 votes
1 answer
144 views

Query-By-Committee with abstention

I’ve some difficulties understanding how abstention works in Active Learning. A teacher asked me to implement the active learning algorithm Query-by-Committee which helps a committee to ask the better ...
MarcAntony's user avatar
0 votes
1 answer
144 views

About update procedure in data incremental learning

As far as I understood, the idea of data incremental learning consists of keeping the model always up to date. Suppose that we trained a model for user recognition using voice as input. Therefore, the ...
Mas A's user avatar
  • 203
1 vote
0 answers
9 views

How to Retrieve Feature Weights and Formula from SVC Classification

I am quite new to skit-learn. I have been working on a SVC Classification problem which seems to be yielded good results. I am using an SVC Polynomial Classifier @ 40 degrees; please see attached (...
Tybalt's user avatar
  • 23
0 votes
1 answer
450 views

Confusion about "online learning" and "data or class incremental learning"?

I saw there are some posts on stackexchange on the subject (example1, example2 and example3). However, in this paper, they use SGD as an online learning model. They state that The incremental ...
Mas A's user avatar
  • 203
1 vote
1 answer
31 views

Affects of including generated data into "real" dataset

I was thinking about what the outcome of the following idea would be. Let's say that we have a Generative Adversarial Network (GAN) that has "successfully" (i.e., Discriminator is not able ...
Angel Adrian Cantu's user avatar
1 vote
1 answer
153 views

Classification ANN accuracy results interpretation

I am currently implementing a simple feed forward ANN to a classification problem with 3 possible outcomes/classes. The results don't look great, therefore, I am currently thinking about whether my ...
J3lackkyy's user avatar
  • 705
1 vote
1 answer
67 views

Clarifications on Generative Adversarial Nets

I have just read the paper https://arxiv.org/pdf/1701.00160.pdf which is a tutorial on GAN. I have a few clarifications: Must the dimension of the output layer of Generator match the input layer of ...
onexpeters's user avatar
1 vote
0 answers
28 views

Recommended machine learning method to solve my problem in sequence prediction [closed]

I am pretty new to most algorithms and with there being so many out there, it is hard to choose as a beginner which one to use. Therefore, I am looking for some recommendations here. The problem is as ...
Jacky Chu's user avatar
3 votes
0 answers
43 views

How can I model this Bayesian learning process of two types of coins?

(As suggested on the comment, I slightly changed my previous question.) I have $N$ coins and I am testing them one by one if it is fair or not. I know that, if it is unfair, the probability of head ...
Anonymouslylost's user avatar
0 votes
2 answers
2k views

Test Accuracy same as Training Accuracy

I am building a prediction model using KNN. After experimenting the data using KFOLD Cross Validation technique, I've got the mean accuracy and applied them on the real model and it turns out that the ...
Kwimori's user avatar
1 vote
1 answer
268 views

Empirical Risk Minimization: why is the rate of convergence important?

In section 4 Empirical Risk Minimzation of the paper Principles of Risk Minimization for Learning Theory by V. Vapnik, the author says the following: In order to solve this problem, the following ...
The Pointer's user avatar
  • 2,002
1 vote
0 answers
18 views

Public data and examples for practicing distribution fitting? [closed]

Are there public data for practicing distribution fitting and examples? I want to practice parameter estimation with various methods. To do so it would be helpful if there are reliable examples of ...
0 votes
2 answers
137 views

Econometrics online learning course [closed]

i would kindly like to ask you for recommendations regarding introductory, but more importantly advanced online econometrics courses (theory as well as applied, preferably in R). I would be most ...
2 votes
3 answers
771 views

How to conduct linear regression with lots of data?

Say we have an absolutely huge dataset, and it's too much to put it all into one linear regression model to train. How can we go about using all of this data? I was thinking that we could break this ...
Jame Flanagin's user avatar
0 votes
0 answers
944 views

Machine learning algorithm for finding most similar entries in dataset

I have a pandas Dataframe, which has data as structured below. ...
Kristoffer Tølbøll's user avatar
2 votes
1 answer
412 views

Convergence under large set of learning rates

What is the interpretation of a stochastic optimization problem where a gradient descent algorithm is converging under a wide range of learning rate schedules (including ones with quite large initial ...
Dion's user avatar
  • 954