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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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synthesized data to train classifier

Our dataset is relatively small (303 x 14) and so we decided to use synthpop package in R. The basic idea of synthetic data is to replace some or all of the observed values by sampling from ...
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Random effects model vs Region by region model - which is more accurate for translating to business action?

I have 100 regions and several features like [quality_rating, the density of stores in a region, the number of people who purchase, age, gender, income, lifestyle], etc. for each region. Let's say my ...
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Features that are important according to random forest are not significant when logit model was used. How to interpret?

I have a feature set for each customer [age, gender, income, lifestyle, & so on...] and a response variable say: has_repurchased. I use a logit model summary which shows income & gender to ...
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Analysis on cluster change

I have 50 datasets each for every year from 1961 to 2010. These datasets keep data about GDP, mortality, natality, etc. My intent is to apply clustering for each dataset and then compare clusters. ...
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What is the scale of pseudo R squared obtained from my Logit model?

I am getting a pseudo R squared in the range of 0.01 - 0.05 when I experiment with various combination of features. I am aware of this post: McFadden's Pseudo-R2 Interpretation says 0.2-0.4 ...
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How to derive a ranking function from observations

I have a employee dataset with the following 5 details. projects completed customer ratings number of bugs reported customer complaints profit I want to rank ...
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16 views

Including the outcome variable in multiple imputation

I'm trying to perform binary classification on a dataset with missing values. I used sklearn's iterative imputer to impute these values and I got pretty good results. However, I realized that I was ...
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Can bagging outperform a random forest?

I want to predict wages and constructed bagged regression tree's and a random forest of regression Tree's. The bagged regression tree's outperform the random forest. Is this result even possible , I ...
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Machine learning for discrete probability distributions when events can be rare

I am following a paper which suggests using a restricted Boltzmann machine for learning a discrete probability distribution. I have encountered a problem, however, when the scientifically "interesting"...
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Oversampling in Uplift Modelling

I hope any of you can help me in the following matter: I am about to write my master thesis addressing the question how response and uplift modelling differ in terms of performance but also the ...
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Asymmetric or unequal misclassification costs in random forest

I have a general question about asymmetric costs. In machine learning problems, there are times when the cost of a false positive is different from the cost of a false negative. Accordingly, models ...
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1answer
344 views

On the convergence of Iterated Conditional Modes (ICM) for MAP inference

ICM is very fast but I could not find any references that contain a detailed analysis on its convergence (e.g. rate of convergence). Any suggestions please? Thanks a lot for your help!
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Proof for asymptotic error in logistic regression

Ng, A.Y., and Jordan, M.I. (2001). On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes. Advances in Neural Information Processing Systems, 14, pp. 841-8, ...
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Using sigmoid in binary DNN output layer instead of softmax?

For a binary DNN, the output is $y_0 + y_1 = 1$ since they are the probability distribution, hence the sum must equate to 1. However, I've been told that $y_1$ is sufficient to represent the output of ...
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1answer
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How to interpret precision and recall for multiclass prediction?

I have a few models doing prediction with 4 classes, with the output precision and recall varying with different labels. For example I have (with the class labels being 0, 1, 2, 3 on the x axis): I ...
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What are other nonlinear transformation methods in machine learning except Neural Network activation functions?

One advantage of the MLP neural networks is the nonlinear transformation used on raw features. The popular ones used are the activation functions like Sigmoid, Tanh, ReLU, Leaky ReLU, etc. They are of ...
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Machine Learning problem - label over multiple lines

Currently I'm trying to work out a project where I would like to recognize movements from videos using machine learning and python. What I've done so far is extracting the x and y values of body ...
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How to calculate accuracy of model without having actual labels

i have a dataset having traing.csv and testing.csv files. i have trained the model on traing data and then predict the labels for testing data. as the labels are only given in training data. there are ...
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Unsupervised Learning: Distinguishing 10 spoken numbers in Arabic

I want to develop an unsupervised learning method to identify spoken numbers in Arabic. My dataset consists of MFCC arrays. Every row consists of an array of shape(41,13), The row consists of float ...
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On Structures in Dataset [on hold]

I am working on a dataset challenge and am being asked to detect structures in the dataset. What are some ways we can define structures within the data? Is that pretty much any patterns found? Maybe ...
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1answer
182 views

How do I optimize decision tree regression algorithm implemented in R?

I'm only getting an accuracy of 59% using the following implementation calculated using the diag(sum(cm)) and sum(cm) functions. ...
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Are feature importances from tree based models directly actionable for business?

If my response variable say is "has_repurchased" [0 or 1] and I have all customer level features. Can I rank the features in order of importance from the random forest model and report them as whats ...
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Modeling both linear and non-linear relationship

Apology for being verbose and all the typos or mistakes. This problem has been bothering me for a while and I really hope you can help me with it. Let's say I want to model quarterly sales for a ...
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How does regularized regression overcome the p > n problem?

So, I understand why simple linear or logistic regression will have infinite solutions in this case (good answers here and here). But while LASSO will only select n features, Elastic net does not have ...
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Question from Machine Learning Textbook on Number of Models

In the James, Witten, et.al Statistical Learning textbook, it says the following: "Unfortunately, there are a total of $2^p$ models that contain subsets of $p$ variables." Can someone please ...
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1answer
375 views

What is the difference between accuracy and AUC score which one to trust?

I've 300 samples with multiclass classification problem with 3-classes. I implemented SVM in R programming. Below is the output which I am really confused. Can anyone logically explain to me what is ...
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1answer
763 views

Hoeffding's Inequality

I am studying the feasibility of learning from the book Learning from Data. The author uses a bin analogy to discuss the feasibility of learning in a probabilistic sense. I have certain questions to ...
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High accuracy on both training and validation but very low on test set

My CNN model has about 96~97% accuracy on both training and validation sets. But when submitting the test set it got only 24% accuracy. Here's my model: ...
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How does rectilinear activation function solve the vanishing gradient problem in neural networks?

I found rectified linear unit (ReLU) praised at several places as a solution to the vanishing gradient problem for neural networks. That is, one uses max(0,x) as activation function. When the ...
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Why f beta score define beta like that?

This is the F beta score: $$F_\beta = (1 + \beta^2) \cdot \frac{\mathrm{precision} \cdot \mathrm{recall}}{(\beta^2 \cdot \mathrm{precision}) + \mathrm{recall}}$$ The Wikipedia article states that $F_\...
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1answer
28 views

Inputting playing card values to aneural network

I am trying to create a NN to play a card game wherein each state is represented by the hands of 4 players. Every round, the hand of each player is decreased by 1 (discarded). Each player starts with ...
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1answer
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332 views

Unsupervised pre-training for Reinforcement Learning

Since the advent of many unsupervised learning methods, as a pretraining step for the main supervised task (mostly under the name of Deep Learning), it shouldn't be strange to ask, what is the current ...
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Recognizing whether a written and spoken number is the same

For our ML assignment we have three datasets. The challenge is about checking whether a written and spoken number refer to the same number. We're using the MNIST dataset with handwritten numbers, and ...
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1answer
4k views

LSTM cell output activation for series

This question is asked from the perspective of finding out if there's a more efficient way for an LSTM to act more as a regression entity rather than just assigning only probabilities to the next ...
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2answers
396 views

Proof of correctness of normal equation

I was taking an online course and saw linear regression being by gradient descent The intuition behind why the method would work seemed plausible. I tried understanding normal equation as to why ...
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1answer
446 views

Influence of word counts from DTM on LDA with Gibbs Sampling

I'm trying to wrap my head around Topic Modeling based on LDA with Gibbs sampling (Griffiths, Steyvers 2004: Finding Scientific Topics). What struck me when reading some Python implementations like ...
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2answers
51 views

Finding Relationship between Categorical and Continuous data

A subset of my dataset looks as follows where cells in "cat1_ids" column contains list of "cat1" categories and cells in "person_id_list" column contains list of persons id. There are 2000 "cat1" ...
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3answers
386 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 ...
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Multivriate Time Series Model - ARIMAX

I have Weekly Units sales data of products for 2 years (104 weeks). And I am trying to forecast the Unit sales for each productid for next 8 weeks.. Please find the data image below. note: Productid ...
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Estimating a changing transit time between inputs and output

I work with a chemical process in which there is a time lag between the inputs (raw material quality and cooking parameters) and the output (final product quality). The problem is that the time lag ...
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1answer
11 views

Calculating a continuous variable with regression trees

I have sample records with several attributes (predictors) and a predicted variable Yes/No. What I need is, given new data that omits the column Yes/No, to know what is the probability of Yes. Note ...
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What is the relation between a loss function and an energy function?

A loss function is a function that measures the distance between the expected value and the actual value of a model (an example of a loss function is the cross entropy). An energy function can be ...
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1answer
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Setting bias of output layer for imbalanced datasets

From a blog post from Andrej Karpathy on training neural networks: Initialize the final layer weights correctly. E.g. if you are regressing some values that have a mean of 50 then initialize the ...
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1answer
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Training Perceptrons with Backprop

Is it possible to train a simple perceptron with a threshold activation function such as this one: https://en.wikipedia.org/wiki/Perceptron with Backpropagation instead of the perceptron rule? is it ...
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Cannot seem to converge beyond a loss of 3 on an object detector being trained on YOLO

Data The you only look once YOLO algorithm is used for object detection. I have scoured the internet for resources on how to tackle this problem, but there seems to be a lot of resources that point ...
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1answer
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What is the difference between policy-based, on-policy, value-based, off-policy, model-free and model-based?

I'm trying to clear things out for myself, there are a lot of different categorizations within RL. Some people talk about: On-policy & Off-Policy Model-based & Model-free Model-based, Policy-...
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1answer
27 views

Why test and training dataset should have same number of columns(variables)?

Why can't i train the model with specific number of varaibles and test it with more or less variables. (i know i will get error when i do this). But what is the resaon behind this? The main concept ...
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How to generate a project plan template from a list of project plans?

Consider the data for 3 users from the same domain: “Design the UI”, “Develop/code the UI” and “Discuss changes with the client” are the most common tasks. The duration could be a simple average. So,...
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Why we use calibration of Machine Learning models?

From the different websites I got to know how to perform calibration of models. But can anyone tell me the reason behind performing calibration of machine learning models?