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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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28 views

“Concept Class” in Machine Learning

I was reading this famous paper and encountered the term "concept class". There's one example given: union of balls in $n$-dimensional space. But one single example is not clear enough. Can anyone ...
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1answer
21 views

Modelling small data set problem

I have a small dataset (20 instances per 13 classes). The 13 classes are human users from their behavior features, I have to classify if an unseen behavior feature is of a user or not. Data: These ...
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1answer
20 views

Continuous loss function that can measure one-side error

I am predicting a target $y$ using regression. In my application, the prediction $\hat{y}$ should be always no less than $y$. If $y>\hat{y}$, it is definitely a wrong prediction. On the $y<\hat{...
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10 views

Optimizing multiple objectives with different scales

I have multiple objectives, such as $f(\mathbf{x})$, $g(\mathbf{x})$, and $h(\mathbf{x})$. I would like to find a set of $x$ that can $\underset{\mathbf{x}}{argmin} [ f(\mathbf{x}) + g(\mathbf{x}) + ...
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1answer
15 views

How to tune the hyperparameters for oneclass SVM while doing unsupervised learning?

For my task, I am doing unsupervised learning and I am trying to find the best possible value of the parameters gamma and nu in ...
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4 views

SVM test data point classification

I am new to machine learning. What if a data point falls inside the support vector margin? Below wx-b = 1 and above wx-b = 0 OR Above wx-b = -1 and below wx-b = 0.
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31 views

What machine learning and deep learning models are used for longitudinal studies (panel data)?

As the title suggets, I have a longitudinal database (also called panel data). (I have over 100.000 observations. The time period is X years. This means that for every year I have the values of the ...
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0answers
19 views

Distance/Metric between two regression models?

I wonder if there is any theory or work about the "similarity" of two regression models. For example, if it is linear regression, the "similarity" could be defined by the l-2 distance between the ...
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18 views

How to handle maxpool layer backpropagation with recurring max values in same position

Say I have a layer a: 3 4 2 1 5 0 8 6 4 The maxpool using 2x2 filter is: <...
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1answer
27 views

Interplay between early stopping and cross validation

I am a little bit confused by early stopping and in particular by how it can be inserted inside a CV framework. As far as I understand, I can fix the optimal number of epochs (for NN, or number of ...
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24 views

Workflow in data preparation with Box-Cox transformation

I have a dataset with both missing values and outliers in continuous features. I would like to perform Box-Cox transformation on every continuous feature to reach the best distribution. Box-Cox works ...
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1answer
73 views

How to pre-process audio recordings for training a machine learning model?

Task: Process audio data so that it can be used for training a machine learning model--which would be used for labeling unseen/unheard audio recording in future. Data: The audio recordings are ...
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3 views

Using NDVI along with regular RGB and NIR bands for image classification

Is it plausible to use NDVI along with other regular bands for image classification related data processing? Recently, I came across a comment that RED and NIR band might interfere with NDVI or vice ...
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9 views

Why do we get contour around dataset when we use rbf kernel in svm?

Why do we get contour around dataset when we use rbf kernel in svm? For example, we use kernel trick to map 2D data into 3D and we can use linear hyperplane to split data, but when we get back to 2D ...
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0answers
7 views

Finding groups of features that meet condition on the response variable [closed]

Given data-set of 100,000 people with 30 independent (mix of categorical, ordinal, interval) attributes, and one dependent continues attribute. More information on the data: Every observation ...
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1answer
30 views

What type of neural network is used for image to restore pictures from pixels

When we have small low resolution, fuzzy image for example: and if it to zoom, an unrelated set of pixels is obtained. For example Tell me, please is there the way to train a neural network to ...
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10 views

Comparing Density Plot height (MachineLearning Classification)

I am working on a binary Machine Learning classification problem. My classifiers are really performing poorly because distribution of the 1 class is very similar to 0 class (dataset is imbalanced, 1 ...
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2answers
28 views

Time series forecasting with hour data, prediction for next 24 hours

i'm a newbie in Time Series Analysis. I have a 2 year pandas dataframe about water consumptions in hour granularity (24 records for day, 365 days). Water_consumptions Data ...
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6 views

data partition for stacking

I try to ensemble some models. I think that if I want to use stacking method, I have to divide data into two-parts. One part is for training first layer models. After training first layer models, next ...
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25 views

Use Shapley Values for explaining whole Data Frame instead of a Single prediction

I am working on a Machine Learning model. One of the requests is to explain the models 'decisions' to the business. Therefore I am using Shapley Values (Game Theory). I found an interesting example ...
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1answer
19 views

How to normalize mutual information between to real-valued random variables?

How can I normalize mutual information between to real-valued random variables using Python or R? ...
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0answers
11 views

Cost-complexity pruning in a classification tree

In a regression tree cost complexity pruning is simply to choose the tree that have the lowest c(T) = RSS + a|T|. In classification trees we use the gini-index or the cross entropy measure as the ...
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37 views

How to deal with an imbalanced dataset for multi-label classification?

You can consider me novice to intermediate at best with Machine Learning. For the past few months, I've been developing a neural network that learns to play a 3D fighting game by trying to mimic how ...
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8 views

Is there a good plug and play method for online/iterative regression in scikit-learn?

I have an independent variable with 19 dimensions(19 features) and I need to perform stepwise regression. I need to perform iterative regression because the target value I am predicting becomes ...
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1answer
12 views

How to make a prediction with Bayes Classifier after computing MLE?

I'm trying to figure out the role of computing the MLE for classification/prediction purposes with the Bayes Classifier. Let's say I'm given a set of data assumed to be Gaussian. I can then compute ...
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1answer
18 views

fitting after training and validation

There are a lot written in StackExchange about train-validation-test split of data set. I am confuse with the following. Assume, I trained model using train set. Then I choose model using validation ...
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11 views

Sequence classification - customer behaviour

I'm working on a classification model for predicting customer behaviour. For each customer the dataset has multiple rows; each row representing information about his transaction during a quarter. I ...
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0answers
13 views

Different metrics for GridSearch and Keras: which one is actually returned

During GridSearchCV/RandomizedSearchCV we have different options to use for scoring, 'accuracy' being the most popular. However, in the case of unbalanced classes, such metrics as "f1_macro" are more ...
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36 views

evaluating logistic regression's performance

I am working on the scoring model and I aim to predict the probability of default. I have, say m, different candidate Logistic Regression models $M_{1}, \dots, M_{m}$ and I would like to choose the ...
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1answer
13 views

Statistical test for cross validation with a low mean

I'm working on comparing 2 algorithms with an experimental protocol that produce 100 folds for each one. As a result, I found that my algorithm got (49.29 $\pm$ 1.69) and the baseline got (50.40 $\pm$...
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1answer
29 views

Is the out-of-bag (OOB) error of a random forest classifier overly optimistic if hyperparameters were learned via CV on the same dataset?

I am training a random forest classifier in a setting with such a low sample size that I cannot afford setting aside validation and test sets. I train the hyperparameters via cross-validation and ...
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1answer
23 views

Categorical feature with one dominant value [closed]

in my dataset for machine learning I have many categorical features with one dominant category as you can see on the picture. How can I deal with this kind of categorical data in preprocessing?
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1answer
45 views

How to prove $P(a \geq b +c) \leq P(a \geq b) + P(c \leq 0)?$

How to prove $$P(a\geq b+c)\leq P(a\geq b)+P(c\leq0)?$$ Thanks.
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1answer
22 views

Is a GAN's discriminator loss expected to be twice the generator's?

If a GAN generator has the same (but reversed) hidden layer architecture as the discriminator, is a the discriminator's loss expected to be approximately double the generator's? In the examples I'm ...
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19 views

Understanding Strength and Correlation in Random Forest

In the original paper of Random Forest, the author introduces a concept of strength and correlation. In the appendix section, a step by step guide to calculating these values are given for the ...
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1answer
23 views

Will a transformed categorical dataset lead to different results?

Suppose we have a dataset, where Y and X are categorical. Y can only take the value 0 or 1. There are two ways how to represent the data (where of course Color and Shape will be factorized i.e. blue = ...
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6 views

What would be the biggest considerations in using an SVM for NLP?

Evaluating a linear SVM on an NLP corpus where there are 150,000 data examples but each language sample is reasonably short(10-15 words). This is evaluated against a code that is a topic. For example "...
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1answer
43 views

Strange accuracy graph

I was training my NN when I found out something I CAN NOT understand. My net is a bilstmLayer and a softmaxLayer layer with 10 MaxEpochs and 150 MiniBatchSize. I want to classify 4 different type of ...
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17 views

Link between norm of weights/coefficients and smoothness

We often avoid overfitting by penalizing the norm of the weights/coefficients (in a classic Ridge or Lasso regression). I understand that we want smooth functions as they will be more likely to ...
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0answers
8 views

Got very poor accuracy whenever I train any deep neural network [duplicate]

I am trying to train a network on Alabone dataset downloaded from "UCI machine learning repository" site. The dataset is look like: ...
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1answer
24 views

How to extrapolate partial curve based on other complete curves?

I heat a room to a certain temperature. Then I let it cool over time. I measure the temperature at 6 intervals as it cools. I repeat this process for some other rooms. From this, I get a set of ...
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0answers
18 views

Prediction Challenge AI. Machine learning and data analysis.(Inconsistency data)

I am working on a personal rento in which based on some input data I have to predict some output data. The challenge is to predict the expenses in transactions, receipts and cards that users will have ...
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1answer
356 views

Imbalanced dataset binary classification

I am new in ML & DS and i have a dataset with an imbalance of 9:1 for Binary Classification,as an assignment. Could you please guide me in this regard? Also Which classifier is best for Imbalanced ...
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0answers
21 views

Is it possible to audit a machine learning system for bias?

More specifically, imagine we were examining a machine learning system for bias in a certain dimension and for simplicity sake it consists of a singular machine learning algorithm. Could we take that ...
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1answer
23 views

Understanding Feed Forward Neural Network

My problem with FFNN is that I do not understand in which use cases this network makes sense. Does anyone have an example where this is used? Once I read on the internet that it could be used for YES/...
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0answers
54 views

How to decide if means of two sets are statistically significantly different given that sets are obtained by a split that maximises the difference?

I have a data set consisting of some number of pairs of real numbers. For example: (1.2, 3.4), (3.2, 2.7), ..., (4.2, 1.0) or ...
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16 views

How does Gaussian process update after adding a new point to the model?

I am using a Gaussian Process model in the Bayesian Optimization setting. Concretely, a gaussian process is built on some initial $N$ points and the model is updated sequentially by evaluating a new ...
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0answers
16 views

Variance-bias trade off in classification and regression trees

I know what the variance/bias trade off is when I am talking about regression problems. Also in this context i understand the technical derivation. But I don't have an idea of the variance-bias trade ...
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2answers
99 views

Validation accuracy vs Testing accuracy

I am trying to get my head straight on terminology which appears confusing. I know there are three 'splits' of data used in Machine learning models.: Training Data - Train the model Validation Data - ...