Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [noise]

40 questions
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Can Neural Networks be trained to smooth values / output the average?

Let's say we have a neural network with one input neuron and one output neuron. The training data $(x, f(x))$ is generated by a process $$f(x) = ax + \mathcal{N}(b, c)$$ with $a, b, c \in \mathbb{R}^+$, e.g. something like feature |…
Martin Thoma
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Training on accurate data versus noisy data

I have data currently available that is very accurate and I would like to train my classification methods on this set of clean data to learn the important markers for distinguishing between classes. But in the future, my trained classifiers will not…
Mathews24
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If my model is overfitting the training dataset, does adding noise to training dataset help regularizing the machine learning model

I would like to know if this is a best practice or not. Can we add noise to the training data to help the model "fit less the training data"; as a result, hoping to generalize better on new unseen data?
I. A
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How to remove noise using morphological filtering

I have two groups of dots that both contain noise between them: The line that separates the two groups in the picture is diagonal in shape. I tried to use morphological filtering on this image to remove the noise between these two groups but…
tamarlev
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Training deep CNN with noisy dataset

I am training a Mask RCNN model with a train dataset that has been generated from some simple computer vision operations (color thresholding) and some morphological filtering. The train set captures around 2387 instances over 1157 images and there…
Gouda
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1 answer

Effect of adding gaussian noise to the input layer in a CNN

I often come across Keras code that adds GaussianNoise to the input, however its not clear to me what advantages does it offer to the learning. input_img = layers.Input(t_x.shape[1:], name = 'RGB_Input') pp_in_layer =…
KarateKid
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What is the loss function defined by Mnih and Hinton in their paper “Learning to Label Aerial Images from Noisy Data”?

In section 3.3 of the paper, they state that they use the cross entropy. Then they define the probability for a label to be a false positive as $\theta_0$ and a false negative as $\theta_1$. They use it to somehow modify the loss function but never…
Borbag
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1 answer

Choosing attributes for k-means clustering

The k-means clustering tries to minimize the within-cluster scatter and maximizing the distances between clusters. It does so on all attributes. I am learning about this method on several datasets. To illustrate, in one the datasets countries are…
Borut Flis
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Which algorithm to use to identify clusters with a similar value?

Here, an example of my problem: 10000 observations of people with several features [age, gender, region, number of sons, ...] and a value to predict "income". There is not a general relationship between features and income, therefore a normal…
A M
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Methods for learning with noisy labels

I am looking for a specific deep learning method that can train a neural network model with both clean and noisy labels. More precisely, I would like this method to be able to leverage noisy data as well, for instance by not fully "trusting" noisy…
Mathias Müller
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1 answer

Remove noise by clustering on which step of pre-processing is better?

I am working on a classification task. The dataset is a UCI data set about machine learning with 200 observations and 2 classes. Part of my model includes the following preprocessing steps: remove missing values normalize between 0 and 1 remove…
motevalizadeh
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How to create a complex Gaussian random noise with a specific covariance matrix

I am trying to generate a complex Gaussian white noise, with zero mean and the covariance matrix of them is going to be a specific matrix which is assumed to be given. Assume i to be a point on the grid of x axis, where there are N points on the…
gurluk
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Paramaeter estimation in noisy conditions with Machine Learning, possible?

Let's take two constants, $\alpha$ and $\beta$, both are given by two functions $f_1(\vec{\theta})$ and $f_2(\vec\theta$) (the model). These functions are known: we have an analytical closed expression, that for a given set of values $\vec\theta$,…
ignatius
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Rprop is too noisy

Is there a way to reduce the noisiness and stochasticity of Rprop (and for that matter the iRprop+)? Specifically, in deep networks (with 8+ layers) this effect starts to become apparent, as the earliest layers are adjusted. This has a massive…
Kari
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Model Tree M5 - Robustness to Data Quality Issues

I am currently investigating the M5 tree algorithm by Quinlan(1992) link here: https://sci2s.ugr.es/keel/pdf/algorithm/congreso/1992-Quinlan-AI.pdf An example of a linear regression model of the algorithm can be seen below: An implementation of the…
chrisper
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