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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Using supply as feature in price predictor model

On a machine learning model that outputs the optimum price of a product (ex: cars listed on some website), would it make sense to use the number of instances of that product as a feature? In the case ...
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Terminology question: distinguishing two meanings of “loss function”?

I've heard people use "loss function" to refer to 2 different things: 1) A real-valued function of a label, $y$, and a prediction $\hat{y}$. 2) A real-valued function of a parameter $\theta$; this ...
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26 views

Why using variational inference to do minimization?

I'm reading a paper on conditoinal random fields. They arrive at a formulation for energy, and they go like this: "minimizing this is intractable" What does that mean? I heard about intractable ...
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Analysing arrays of image data with Machine Learning Models

I am trying to do Machine Learning on arrays or vectors describing images. The target variable is a category I am trying to predict. I have multiple features that each contain arrays describing the ...
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Extracting metrics from natural language

Imagine a text like The revenue amounted to mEUR 124 during the year while last year it resulted in mEUR 100. I want to use ML methods to extract two outputs like ...
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Does a pca plot gives me a relationship about my future importances?

I am searching for outliers and wanna have some graphical support. Let's assume I have a original dataset with several columns (numbers for example 7). And I do a pca decompisation. So my code would ...
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Reference: Data-Dependent Early Stopping Criterion for Deep Learning?

In the context of non-parametric regression, this paper provides an data-dependent rule for optimal early stopping, when learning an unknown function $f^{\star}$ lying in some RKHS. Here, one stops ...
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25 views

Why NN works better SVM? [closed]

is Neural Network Ensemble give best prediction over other prediction models or algorithms? If yes, what type of Neural Network?
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Derivation of Bayes classifier in Murphy's book

I am reading Kevin Murphy's Machine Learning book (MLAPP) and want to know how he got the expression for the Bayes classifier using minimization of the posterior expected loss. He wrote that the ...
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Could someone use this concrete data set to illustrate how to compute the average Gain?

Chapter 3, Page 86 of Tom M. Mitchell. Machine Learning (free) says One practical issue that arises in using GainRatio in place of Gain to select attributes is that the denominator can be zero or ...
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Classification with features of similar (semantic) significance

I am working on a classification project. The data was collected in an experiment where each subject (i.e. child participating in the experiment) was shown one drawing at a time, and was requested to ...
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What is best practice when standardizing a truncated numeric variable with lots of zeroes?

What is best practice when standardizing truncated numeric variables with lots of zeroes (like 80% of the obs.)? To provide an example, I have a variable counting number of days per year several ...
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Why do we penalize individual example divergence in variational autoencoder?

In variational autoencoder, we want to learn a mapping between input space $X$ and latent space $Z$, and $z\in Z$ is related to $x\in X$ with $z\sim MVN(\mu(x), \Sigma(x))$. In addition, we desire ...
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Compute gradient after bitwise OR [closed]

I have to calculate the Intersection over Union (IoU) of two segmentations. For that, at some point I have to calculate the bitwise OR of two tensors. I am doing this with ...
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Finding Overlapping Topic Clusters in Labeled Text Data

I have a dataset which consists of two heavily interconnected classes. One is about "Cognitive Linguistics", and the other is "Not Cognitive Linguistics", both are under the umbrella term "Linguistics"...
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26 views

Can I apply PCA on continuous data and reduce the dimensions and keep categorical data as it is?

I have a dataset which contains 95 highly correlated continuous variables and other 3 categorical variables. I want to reduce the dimension of the data and by that I can deal with correlation as well. ...
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Signal Embeddings using the skip-gram or CBOW model

So my work involves looking at a bunch of waveforms in the context of classifying events. I often am looking for new ways to represent my waveforms, and in my searching, I came across audio embeddings ...
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How to estimate the marginal distribution of binary dependent variable with respect to one predictor using a classifier?

I have a dataset with a binary dependent variable $y \in \{0,1\}$ and a set of predictors $x1,x2,..,t$. Here, $t$ is the time in minutes (in 24 hrs, that is $t \in (0,1440)$). I want to estimate the ...
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How to evaluate whether model is overfitting or underfitting when using cross_val_score and GridSearchCV?

This is something that has been written about extensively, but I'm just confused about a couple of particular things which I haven't found a clear explanation of. When cross validation is not used, ...
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Regression Tree in time series

I'm having problem using regression tree (using LightGBM) for time series forecasting after differentiation "T = (T - T-1)". Below is example for reproducing the problem. ...
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26 views

Imbalanced data classification with GLM giving very poor results

I have a loan defaulters dataset and it is highly imbalanced as shown below: 0 1 33108 673 I have tried SMOTE to balance the dataset, as shown below: ...
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29 views

Interpretation of a deep neural network [duplicate]

I am an economist so my academic career has been spent on interpreting beta hat rather than optimising y hat. But I've become quite fascinated by neural networks so I wanted to get some things ...
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Combining continuous and binary data in unsupervised learning

I am working on cluster detection in a data set consisting of housing data. Each data point has some continuous features, such as house size, and some discrete ones, such as the number of garages (0 ...
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PCA's component naming [closed]

HI how to change component names of PCA as by default the names of principal components are 0,1,2....etc for PC1, PC2 etc. I also want to know how to choose features to pass to pca as inputs.Which are ...
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20 views

Machine learning classifier with only categorial predictors [closed]

I have a data set with a binary outcome variable and only binary dummy predictors. Which are the best algorithms for this type of classification task? Is there a code for plotting the results (i.e. ...
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Changing the movement of the window in spectogram [migrated]

What I would like to do is to plot the spectogram of a given timeseries. My problem is: I don't want to move my window for calculation of the amplitude of the frequences by 1 index, but by for ex. 128 ...
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1answer
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How do you train a model on a dataset that's unlabeled but we know the percentage of every class?

Say we have a data set that's pictures of apples and oranges, but we don't know which is which. However the data is organized in such a way, that for some groups of images we know how many of them are ...
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25 views

How do I interpret the paired t-test results?

How do I interpret these results? Which food does the Corvid like best? What does the p-value and t-value mean? Is this test significant? My hypothesis is: H0 Corvids have no preference on food ...
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1answer
19 views

Could someone please give an concrete example to illustrate how exactly validation set be used for pruning a decision tree?

Chapter 3 of Tom M. Mitchell. Machine Learning (free) says: the available data has been split into three subsets: the training examples, the validation examples used for pruning the tree, and a set ...
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1answer
34 views

Using data from multiple sources with same features in classification problem

Suppose that I am doing a classification problem where I classify people into two categories as bullied or not. In such type of ...
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13 views

How to statistically compare the performance of machine learning regression algorithms?

Let say that I want to compare the performance of XGBoost vs NN, or NN vs NN, or even the same NN at different epochs for a regression task. All algorithms are trained and evaluated on the exact ...
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How do I know I divide dataset into training set, validation set and test set in a correct/appropriate proportion?

Chapter 3 of Tom M. Mitchell. Machine Learning (free) gives this advice: One common heuristic is to withhold one-third of the available examples for the validation set, using the other two-thirds ...
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How high is multiclass AUROC too high?

Whenever I get AUROC above 80% for a binary classification problem I do my best to check for leakage and overfitting - and usually my intuition is right, true AUROC is closer to the 70%-75% range. ...
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24 views

What are number of hidden layers in LSTM?

I new to LSTM. I have not understood some terms used while implementing it in tensorflow. So I have ECG data, with each event having 60 heartbeat templates with each heartbeat template having 600 data ...
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72 views

What are some of the technical limitations of NMF compared to PCA? [closed]

Apart from NMF not being able to work with non-negative data, what other technical limitations does it have in comparison to PCA, when reducing the dimensions of a dataset? Thanks
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1answer
69 views

Why am I getting accuracy of 100 percent using SVM

I am working on Credit card data set for fraud detection. When I apply SVM for it, I am getting the accuracy as 100 %. What might be going wrong here? Here is the code ...
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40 views

What criteria would you used to choose the greatest number of metagenes when factorising an input matrix into two matrices? [closed]

I am learning about NMF in R. But I am curious which criteria could I use to choose the best number of metagenes when factorising an input matrix (V) into two matrices (V ~ WH)?
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1answer
16 views

How to rank data based on cross-validation

I had this problem from a long time. I have small dataset with about 1000 data points. The data is labeled as 1 or 0 (i.e. ...
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24 views

Can dev (development) set be part of a training set in machine learning? [duplicate]

I split the full data into training and test set in 80:20 ratio. Then within the training set I randomly carved out 10% and called it the dev (development) set. In the dev set, I select features and ...
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37 views
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Choosing learning rate with 2nd order method - minimizing parabola in one step?

In parabola $(\theta,g)$ values are in line $(g=f'(\theta))$ - we can get slope of this line e.g. by dividing their standard deviations: $$ \mu = \frac{\sigma_\theta}{\sigma_g}=\sqrt{\frac{var(\...
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12 views

Why meta labeling is helpful? [closed]

I saw this technique in the book "Advances in financial machine learning" but I found that it acts like a filter for the trades only. And it seems doing the job of overfitting past data by filtering ...
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What does a decision tree hypothesis look like?

I am learning Tom M. Mitchell. Machine Learning (free). in Candidate-Elimination algorithm, a single hypothesis looks like $<Sunny, ?, ?, ?, ?, ?>$ there are three hypotheses in FIGURE 2.1 in ...
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1answer
17 views

Missing name in confusion matrix?

In a confusion matrix, what's the name of the percentage of cases I predict as positive out of the total population? I am in the position of having to use this metric for my project, but I can't find ...
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11 views

Preprocessing during a Kfold cross validation

I have noticed from various sites online that preprocessing and feature selection when dealing with Kfold Cross Validation suggest that the preprocessing and feature selection should be done on the ...
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31 views

How to change the distribution of classes?

I have two classes [0,1] and I want to evaluate algorithm on different distributions of classes. I did label flipping incrementally such as 0%, 10%,20%,....,90%,100%. Does label flipping change the ...
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14 views

transformations of empirical distributions for multi class logistic regression

I am working on a multiclass logistic classification problem where two of the predictors (features) have highly skewed distributions. One is visibility (in m), which looks something like this: ...
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Maximum level of label noise for binary classification so that dataset is “Learnable”?

Assume we have an imbalanced dataset (minority label frequency 1-20%), where subset of samples have their labels randomly flipped. Now, of all samples with positive label (the minority class) in this ...
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1answer
32 views

Random Forest classifier with mean accuracy of 1? Sounds fishy

I have a small dataset with many features, but unfortunately only 19 observations from 2 categories. The idea is that I can determine feature importance in classifying samples in one of 2 categories. ...
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1answer
22 views

How can I separate the overall variable importance values when using Random forest?

I implemented a random forest model in R using the package 'ranger' combined in 'caret' package with 10fold CV. My outcome is binary (0,1) and I have a couple numeric predictor variables. I used the ...
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12 views

Implementing a Kernel Adaptive Filtering model explained in a paper

In this paper, Stock price prediction using kernel adaptive filtering within a stock market interdependence approach, the authors propose a method for predicting stock prices by combining the ...