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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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Why using RMSE as loss function in logistic regression takes non convex form but doesn't in linear regression?

I am taking this deep learning course from Andrew NG. In the 3rd lecture of 2nd week of the first course, he mentions that we can use RMSE for logistic regression as well but it will take a nonconvex ...
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How to add regularization term lambda?

I have this equation in online-sequential extreme learning machine. how can include a multiplication regularization term lambda to govern how rapidly the network weights update please any help. ...
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Implement the probability distribution function of a dataset and calculate the Mahalanobis distance of any given new instance [duplicate]

I'm looking for some practical guidance, as I have a limited time to go from theory to implementation. I would appreciate concrete recommendation on libraries, tutorials or similar to implemente a ...
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Method to identify recurring patterns (motifs) in a time series after giving a reference pattern

I would like to know if there exists an algorithm using which I would be able to extract repeating patterns from a time series dataset, provided I give it a reference shape. I have included an image ...
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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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9 views

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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5 views

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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1answer
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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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12 views

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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23 views

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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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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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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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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1answer
15 views

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 [on hold]

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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19 views

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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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
53 views

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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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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2answers
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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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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 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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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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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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1answer
25 views

What units is my mean squared error if I center and scale my training data?

I have a KNN model that I used to predict the close price on houses. ...
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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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16 views

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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5 views

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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0answers
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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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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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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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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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23 views

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?
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1answer
28 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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Do unbiased regression coefficents yield better prediction?

I ask myself if a have a omitted variables bias in my regression modell the coefficients of the model are biased so the mse growth because this coefficents are biased right? So does it mean if i ...
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Datasets for Document Classification problem [on hold]

I am doing a project to make a application that can take pdf and docx documents as input and classify them into various categories such as - Financial - Government and Political - Sports and ...
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0answers
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KNN works in `class` but not `caret` (Too many ties) [on hold]

I am making a KNN algorithm to predict close_price with about 80,000 rows of this data. ...
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16 views

What does the intercept represent in a model matrix?

I am making a KNN algorithm to predict close_price with about 80,000 rows of this data. ...
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0answers
25 views

relation among loss function / MLE / Bayesian estimation

I have read a lot of stuff on the relation between minimizing a loss function / maximizing the likelihood / choose a centrality measure of the posterior (Bayesian estimation); but I cannot see a clear ...
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0answers
17 views

Haul's Correlation-based Feature Selection (CFS) formula spread

I want to use the Correlation-based Feature Selection (CFS) proposed by Haul. I found this formula where $r_{zc}$ is the correlation between the summed components and the outside variable, $k$ is ...
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23 views

Is Stochastic Gradient Descent sensitive to training permutation?

I've recently read that SGD (Stochastic Gradient Descent) is one of the most popular techniques for training Machine Learning algorithms, including DNNs (deep neural networks). However, my ...
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13 views

What is parameter chaining in CNN?

I have read an article about the benefits of CNN. One of the points was "parameter chaining". What does it mean? And how does it make CNN more convenient?
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1answer
33 views

What are general practises used to divide the data into training / dev and test set?

Example: I have am building a dog vs cat classifier and I have collected data from 15 countries. Europe: 1. UK 2. France 3. Germany 4. Italy 5. Finland Asia: 1. India 2. China 3. Japan 4. Russia 5. ...
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1answer
31 views

How can I visualize and correctly interpret the multi-output of a random forest regression?

I have multiple inputs and multiple outputs for a model I am trying to build using SkiLearn's Random Forest Regression in Python. I have imputed the missing data, divided the columns where the Ys ...
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What to choose?ML project or an Internship? [on hold]

This is slightly off topic but pretty serious for me. I am an undergraduate student in CSE, 3rd year. I am confused in whether to do internship or to make my own project in Machine Learning in my ...