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.

Filter by
Sorted by
Tagged with
8
votes
1answer
142 views

Does machine learning on random situations require a cryptographically-secure random number generator?

I'm working on a project involving using machine learning to figure out optimal strategies to play board games, and after a few rolls of the virtual dice a thought hit me: For the games that involve ...
0
votes
0answers
6 views

Difference between MABs and full MDPs

As far as Im aware, the difference between Multi-armed Bandit problems and full MDPs is that in MABs the full distribution over the results of action are known. Is this true?
1
vote
0answers
8 views

Adjusting thresholds to achieve higher recall - ethically allowed or not?

When I run an SVC(rbf) model with 5 fold cross-validation I get a mean recall of 0.5272727272727273. Of course this number is low so I want to make the model more liberal in selecting the positive ...
0
votes
0answers
12 views

Not able to plot box plots separately [closed]

I have lot of features in my data and I want to make a box plot for each feature. ...
1
vote
1answer
292 views

Will Boosting reduce variance?

I've seen two conflicting arguments: In a Stanford cs229 note, the author claims that boosting will increase variance (see section 2.5): http://cs229.stanford.edu/notes/cs229-notes-ensemble.pdf Prof. ...
1
vote
0answers
34 views

One Statistic to take account of absolute value, absolute mean difference and the percentage deviation between two different mean

I have a unique problem. I am looking to quantify the difference between two temperature value of different components. I am looking at three statistic to see that difference Absolute mean difference ...
2
votes
1answer
171 views

Including previous predictions as features in time series forecasting

I have a time series that I am trying to model using a Random Forest of regression trees as part of the scikit-learn ensemble library. In order to prepare the model for forecasting, I have included as ...
1
vote
0answers
19 views
+50

Overview of the main methods to prune decision trees

Could someone explain the main pruning techniques for decision trees. So something like the 3 most common techniques with a short explanation of how they work. I have looked online but this, ...
0
votes
0answers
24 views

Linear model has low adjusted R2 [closed]

I am trying to build up a linear model in order to financially explain gold. To be able to identify the correct indipendent variables, I did a correlation analysis between a few variables vs gold and ...
0
votes
1answer
25 views

How to do Data Augmentation and Cross validation at the same time

I have read somewhere that you should not use data augmentation on your validation set, and you should only use it on your training set. My problem is this: I have a dataset with few samples. I split ...
0
votes
1answer
256 views

Splitting Stock Price data for SVM classification

I'm trying to use SVM to predict whether the price of a security will go up in the next 7 days using a prediction of the last 14 days of data. So far, I have extracted a dataset with 15 features and ...
1
vote
0answers
32 views

The effect of multiplying the weighs of a trained neural net with a scalar

Can somebody give us some intuition on why (sometimes) multiplying the weights of a trained neural net with a scalar $s \geq 1$ doesn't changes the accuracy, but multiplying the weights by an scalar $...
1
vote
0answers
38 views

High cross validation score but low model performance on test set

I'm doing a machine learning project and need to predict a user's credit default probability. I tried some simple automated feature engineering and got a good AUC score on training set using ...
0
votes
0answers
33 views

What's a range of good F1 scores?

I have watched a lot of videos on machine learning and in terms of F1 scores, all are different. One video says that an F1 score of .8 is bad, but another says an F1 score of .4 is excellent. What's ...
1
vote
1answer
29 views

Interpreting the Results of a Placebo Refutation Test in the Context of Double/Debiased ML Model (DoWhy)

Say I run a double/debiased ML model which estimates the casual impact of a treatment variable T on Y as being +\$100 with a 95% C.I. of +/- $10. Attempting to refute this estimate, I run the model ...
0
votes
0answers
12 views

Factor levels different in Training and Testing data in ensemble models

The problem is as follows: (I did all of this in R in case it will make any differences) I have a df with $\sim1000$ rows and $122$ columns (variables), in which the last column is my target variable. ...
3
votes
1answer
222 views

What does an expectation with respect to a policy mean in the reinforcement learning value function

I would like to know what the formal definition of the following expression is $$ V_\pi(s) = \mathbb{E}_{\pi}(G_{t+1} | S_t =s) $$ What does it mean to have the policy in the subscript? How would I ...
2
votes
0answers
19 views

What are the state of the art optimization methods for neural networks?

Neural networks are usually trained with first order gradient methods and it's variations such as: batch gradient descent, stochastic gradient descent, momentum based gradient and so on.. However ...
1
vote
0answers
20 views

How do you count the number of parameters for AIC?

Suppose I have an $n$ by $10$ data matrix $X$ and a continuous target $y$. I want to compare 2 models: $m_0$, which is an OLS regression model, and $m_1$, which is a deep neural network with $10^6$ ...
0
votes
0answers
4 views

Independence of groups within a single predictor variable

Say I have two variables: 'Sale Price' of a house, and 'Overall Quality' which is an ordinal variable with values between 1 and 10 (1=lowest quality, 10=highest quality). I want to perform an F test ...
2
votes
1answer
21 views

Time series or features engineering?

I'm hesitating between these two techniques for business data (activity logs, purchases) for classification: I take all the data and consider it as a multidimensional time serie and use a deep ...
10
votes
3answers
449 views

What do statisticians mean when they say we do not really understand how the LASSO (regularization) works?

I've been to a few statistics talks recently on the Lasso (regularization) and a point that keeps coming up is that we do not really understand why the Lasso works or why it works so well. I am ...
0
votes
0answers
12 views

Bad predictions for unbalanced data

I'm studying the behavior of machine failures in a production scenario. For this, I generated random data to form my imbalanced training set, consisting of categorical data, which indicate whether or ...
0
votes
0answers
23 views

Why not use line search in conjunction with stochastic gradient descent?

I'm familiar with numerical optimization in Engineering context. I have taken several graduate level engineering optimization and operations research courses. I'm beginning to learn machine learning. ...
3
votes
1answer
45 views

What is better: Cross validation or a validation set for hyperparameter optimization?

For hyperparameter optimization I see two approaches: Splitting the dataset into train, validation and test, and optimize the hyperparameters based on the results of training on the train dataset and ...
0
votes
0answers
8 views

Why NARX neural network and Hammerstein-Wiener model perform badly than simple sigmoid network nonlinearity estimator on any predictions? [closed]

I am currently working on dynamic modeling and exploring different techniques and algorithms to deploy a dynamic time-series black-box model. My data looks like the following: I have 7 inputs and 1 ...
0
votes
0answers
24 views

Does regularized online machine learning exist?

For tikhonov regularization, we add a regularization term to the least squares objective function for numerical stability. In online machine learning you minimize the regret which is just a difference ...
0
votes
0answers
27 views

Various Methods to Calculate Linear Regression [duplicate]

I have just started learning Machine Learning and one of the very first topics that I have encountered in this venture is Simple Linear Regression. From Andrew Ng's course, I have learned to perform ...
0
votes
1answer
214 views

Approximating SVM using Perceptron

Suppose that we have a set of linearly separable data and this pseudocode of Perceptron: ...
1
vote
1answer
31 views

Mean Square Error and Gradient Descent

I am trying to learn gradient descent and in the course of so I am trying to find the optimal m and c value for my model, for $y=mx+c$ For that, I have plotted the MSE using the below code in python <...
0
votes
0answers
3 views

How to compare estimators for consistency between in-sample and out-of-sample fits?

What general procedures are out there for quantifying how well an estimator (such as for the mean, standard deviation or correlation) of a continuous random variable gives a consistent picture of its ...
0
votes
0answers
21 views

Adjusting OverAll Time Performance using sectional Times

Assume I have two runners, Runner_1 is the average runner and Runner_2 is Usain Bolt. We let the two runners compete in 3 different races on a 100m distance. We assume that the benchmark time for 50m ...
1
vote
1answer
41 views

How to deal with the categorical variables with few data for prediction

The image below shows how the rating for the heating quality will affect sale price.The data is about apartments and it's properties. E.g Rooms, GarageSize, BasementSize, etc. This visualization will ...
1
vote
1answer
22 views

How to use labeled and unlabled data together in machine learning

Say I have a dataset of labeled elements and an unlabeled dataset that I would like to apply my machine learning model to after training. How would I go about reporting accuracy/ROC AUC/etc. in this ...
1
vote
0answers
9 views

Some Confusions Regarding Variable Importance Extraction of Several Machine Learning Models

I'm trying to apply several machine learning algorithms in R using caret (decision trees, ensemble methods (bagging, boosting, ...
0
votes
0answers
10 views

RBF Network for classification

I would like to know how it is calculated the outcomes (i.e. the output layer output) of a RBF Network for a classification problem. My code fits the hidden->output weights with linear regression ...
2
votes
0answers
624 views

Determining alpha for pruning trees with cross-validation

following the answer from of Steffen to the question below: How to choose $\alpha$ in cost-complexity pruning? and slide 10 in: https://web.stanford.edu/class/stats202/content/lec19.pdf I'm still ...
2
votes
1answer
186 views

Force directed graphs vs. diffusion maps vs. t-SNE vs UMAP

Can you help me with a conceptual explanation of how force directed graph drawings work compared to other methods in the context of dimensionality reduction for visualization purposes? In particular, ...
-1
votes
0answers
25 views

What is the purpose to have fully connected layers? [closed]

What is the purpose of a fully connected multi layer perceptron in which every input is connected to every output by a weight? After all, the information is only distributed over several channels, but ...
5
votes
1answer
83 views

Is double machine learning doubly robust? If so, how?

Is double/debiased machine learning doubly robust to endogeneity? I have heard about using double/debiased machine learning for causal inference (Chernozhukov, et al 2016), and even played around with ...
0
votes
0answers
29 views

Model adjustment during cross-validation

I have an imbalanced dataset, with the following stats: Value Count Percent 0 133412 97.62% 1 3247 2.38% I have created a ...
4
votes
1answer
443 views

A statistical test to measure the importance of features?

I'm currently trying to assess importance of the features for my classifier. The situation is the following: first I train my classifier with all of the features I have and tested on a test set . Then ...
2
votes
2answers
79 views

How to read equations in DL/ML research papers

I'm a junior in Computer Science. I have been learning about DL/ML on my own for almost a year and a half. A couple of months ago, I started to read research papers, and I have difficulty reading them ...
1
vote
1answer
16 views

Correct way (if any!) to apply preprocessing to hold out dataset

After cross validation and grid search the below are the desired pipeline steps and hyper-params for my model. ...
0
votes
0answers
20 views

Anyone can give me examples of applications of Belief Propagation?

I've been reading about BP and the theory sounds very very very simple, but I still cannot apply BP in a real situation such as regression problem. Can anyone show me how to do that?
0
votes
0answers
10 views

Longitudinal Analyses - Attrition

I am interested in conducting longitudinal analyses on a cohort that has data collected on them across several time points from 3 to 12 months. At baseline, I have a sample size of 75, but at 3 months ...
0
votes
0answers
4 views

How does Adaboost increase the weight of the Data Instance in case of Regression

I know how the weights of the data Instances increases for all the data which were wrongly predicted in case of AdaboostClassifier, however i did not understand how the Weight of the data point ...
0
votes
0answers
24 views

Statistical test for Tweedie distribution

Is there any statistical test to test whether a highly skewed dataset follows the Tweedie distribution? I am asking this question because I have a highly skewed target variable and I am not sure it is ...
3
votes
3answers
570 views

Is there any Generative Model which can be used for Regression problems?

I've been researching Generative Models recently, and Probabilistic Graphical Models. Every time I read about Generative Models, I see they're trying to predict $P(x,y)$ or equivalently $P(x|y)$ and $...
7
votes
3answers
2k views

Difference between supervised machine learning and design of experiments?

I'm an experimental physicist by training and have used standard statistical methods to analyze data, and the design of experiments (DOE) framework to develop models of systems by varying inputs and ...

1
2 3 4 5
309