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Questions tagged [machine-learning]

Methods and principles of building "computer systems that try to automatically improve with experience."

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59 views

How to extrapolate training metrics to test dataset?

i have split my training data 30/70 and trained models, my models are performing really well on the training set but i have a large unlabelled dataset where i want to do inference, how could i measure ...
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0answers
17 views

RMSProp Squared Gradients

In the RMSProp algorithm (And similar algorithms) that are used in Machine Learning in the subject of Adaptive Learning Rates, the squares of the gradients are used in the algorithm step. Is there ...
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0answers
5 views

Why goal of PLA can ignore the norm of normal vector

Define hyperplane $w*x+b=0$, the goal of PLA(Perceptron Learning Algorithm) is minimizing the distance of misclassified points to the decision boundary, i.e. $$-\frac{1}{||w||}\sum_{i\in M} y_i(w*x_i ...
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0answers
10 views

Learning Rate impact on model building time

I wanted to know that does learning rate impact the model building time in case of Gradient Boosted Trees. I do understand that increasing the number of trees have an impact( more the trees, more the ...
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0answers
32 views

Interpretation of box-counting method from R

I tried to calculate the fractal dimension of a dataset using the box-counting method with R programming. I used two packages: The first one is fractaldim, ...
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1answer
64 views

why has author divided by 1.5 in hands on machine learning with scikit learn

I am reading Hands-On Machine Learning with Scikit-Learn and TensorFlow (76/718), and the author is talking about dividing the dataset into a test set which i follow, but then goes on to talk about ...
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0answers
20 views

can you help me figure out this smart f1 function? [closed]

Hi all this is a function being used to evaluate ML results y_true is the ground truth and y_pred are the predicted values from the machine learning model. This smart F1 function calculates the right ...
3
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1answer
48 views

what could cause these bizarre ML results? [on hold]

I have a large set of images that I want to classify as "happy" or "sad". Each image is also tagged with the distance from the camera to the object being photographed, but for complex reasons, I'm ...
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0answers
15 views

How can I get RMSE from RMSLE [duplicate]

Is that correct If I take e^RMSLE will the resulting value give me RMSE or I am missing sometihing . I want to interpret RMSE from RMSLE
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1answer
14 views

ML Sampling question - Can I increase sample size of current dataset with older copies that have changed over time

I am working on a multinomial machine learning algorithm that labels stocks with buy/sell signals. My code updates with the most recent quantitative data about the stocks daily, so obviously the data ...
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0answers
9 views

forward sampling for Bayesian network with continuous variables and equation-based causal relationships

I have a physical system which can be represented by the following Bayesian network. It has the following characteristics 1) The encoded variables are continuous variables 2) The causal ...
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0answers
15 views

Is it possible to use q learning to achieve machine reading? [closed]

I'm playing with ideas and wondering if it's possible to use q learning for machine reading and answering questions. I'm a beginner in AI even though I've programmed other things for many years, if ...
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0answers
23 views

how to model string pattern to character occurence in deep learning

In my question on stackoverflow, I was trying to decode concatenated string into partitions for example, ...
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0answers
13 views

Unsatisfactory prediction error - is it possible to improve accurancy? [duplicate]

I'm green in ML field and I try to classify user reports to valid/invalid. My dataset contains of Valid - 7355 samples Invalid - 6285 samples So, I devide data into train and test ...
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1answer
123 views

Variance of average of $n$ correlated random variables

Reading about deep leaning, I came across the following formula. $$ \mbox{var} \left( \frac{1}{n} \sum_{i=1}^{n} X_i \right) = \rho \sigma^2 + \frac{1-\rho}{n} \sigma^2 $$ where $X_1, \dots, X_n$ ...
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1answer
16 views

How to estimate the leafsize of the kd-tree?

The kd-tree implementation proposed by the scipy python libray asks for the value of the leafsize parameter that is to say the maximum number of points a node can hold. It is by default set to 10. ...
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1answer
23 views

Is a polynomial kernel ridge regression really equivalent to performing a linear regression on those expanded features?

Say we have a dataset, X, which is Nx2 where N is the number of examples and 2 is the number of dimensions "features". If we were to run a kernel ridge regression (or SVM or whatever) on these ...
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0answers
22 views

$L^2$ Regularization and Hessian Matrix [duplicate]

In the second paragraph it is mentioned that eigenvector of $H$ is rescaled by a factor of $\frac{\lambda_i} {\lambda_i +\alpha}$ What exactly meant by that ?
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0answers
26 views

Best approach for learning Reinforcement Learning coming from economics?

I have an economics background so I have have Calculus, Linear Algebra, Diff. Eq., 2 semesters of Stats and Prob. and some Python Knowledge. My school offers a 2 months postgraduate course in ...
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2answers
25 views

Meaning of Probability Distributions in RBMs

I'm new to machine learning, and am trying to understand some of the basics of Restricted Boltzmann Machines. Unfortunately, I don't have a background in statistics yet beyond a basic understanding, ...
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1answer
14 views

Understanding `score` in LightGMB

I'm newly introduced to the LightGBM for a regression problem. Having read the documentation of LightGBM (here), I got puzzled about the ...
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0answers
9 views

Replacement for angular distance metric

I am looking for a distance metric that could be used instead of cosine/angular distance for high dimensional data. Metric that is limited the same way as cosine/angular distance is would be great. ...
1
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1answer
65 views

Understanding Rejection sampling

In acceptance rejection sampling, what is the intuition behind using the formula for finding c( a constant that envelops the target density function): $$c\geq derivative\left(\frac{target\ ...
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0answers
11 views

Generalization and Over fitting

I am reading the book Deeplearning by Goodfellow. There it explains about three factors about generalization, which I find it quite blury to imagine. Excluded the true data generating process—...
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1answer
12 views

Presenting results of SVM model following LOOCV

I have a small dataset of 60 points and used an SVM regression model (with linear kernel) to train a model to predict $\bf{y}$ from two features, $\bf{x_{1}}$ and $\bf{x_{2}}$. I used LOOCV to provide ...
2
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1answer
23 views

How a stationary time series forecasts non-stationary values?

In time series data, non-stationary data is first made stationary (Using Differencing or any other methods). We train the model using this stationary data. So how come model's forecast will be close ...
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0answers
31 views

Fixup initialisation for residual networks

In their Fixup Initialization: Residual Learning Without Normalization, authors suggest: Fixup initialization (or: How to train a deep residual network without normalization) 1. Initialize the ...
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0answers
19 views

Calculating the true error comprised of two probability distributions

Let $X$ = {0,1,2,3,4} and $Y$ = {0,1}. A probability distribution $D$ defined on $X\times Y$ such that $D_x$ = Binomial(4, 0.5) and $D_{y\mid x}$ = Bernoulli(0.5). Given the predictor: $h(x)$ = $0$ ...
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0answers
13 views

Confidence interval for sum(observed) (continuous, right-skewed) divided by sum(expected) (continuous, right-skewed)

I need confidence intervals for an o/e metric based on a continuous variable (observed days/ expected days) sumed up for all the people in the population.
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0answers
10 views

What are the advantage of using Sigmoid and Softmax and disadvantageous of both? [duplicate]

I am trying to understand the architecture of the neural network. I am supposed to make decision of how many hidden layers and what activation functions to use in the hidden layer and which activation ...
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1answer
20 views

Mix of categorical and continuous data in neural network

Given a shallow or deep neural network, how would one go about using both continuous numerical input features and categorical features? For example, given a network that receives a set of 100 ...
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1answer
16 views

When the validation set is a subset of the training set

I am doing the following but I am not sure if this is right or which behavior should I expect: A union B union C is the full dataset Training set: is A union B datasets Testing set: is C Validation ...
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0answers
11 views

How to reach streaming learning in Neural network?

As title, I know there're some model supporting streaming learning like classification model. And the model has function partial_fit() Now I'm studying regression ...
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0answers
20 views

compare the outputs of two different ML models

Let's imagine I have two completely different multi-class ML models, let's call them ML1 and ML2. The models were trained on completely different data with different target classes. As an output, the ...
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0answers
7 views

Model Training and test accuracy suddenly dropping for a Mulit Layer Perceptron from 98% to 9% (test)? [duplicate]

I was exploring the tensorflow library and was working on an MLP for the mnist dataset. It is 5 layers MLP trained for 10000 iterations on batches of 100. After training the model up to 9000 ...
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0answers
24 views

Dummy variables with dummyVars() - return to original columns [closed]

For building a machine learning model I used dummyVars() function to create the dummy variables for building a model. ...
3
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2answers
93 views

Object Localisation without Classification

I have a data set of photos containing an object in each of them. I want to find out the coordinates of rectangle enclosing the object. Note that each photo contains exactly 1 object (for example, if ...
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0answers
26 views

How to Fine Tune a pre-trained network

I'm looking into using Transfer Learning to take the ResNet50 model trained on ImageNet and fine tune it to my own dataset using Keras. However, I feel I have some misconception about what exactly ...
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0answers
14 views

compute the KL divergence between two datasets

I have two datasets $D1$ and $D2$ in two different feature spaces $\mathcal{X}_{1} \in \Re^{m}$ and $\mathcal{X}_{2} \in \Re^{n}$. Further assume that the datasets have different number of data points....
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0answers
31 views

What if the best k in k-NN is equal to the number of data points?

I need to train a regressor (in the machine learning sense). I have tried many different methods and so far nothing works better than just a constant prediction. In other words in looked like I have ...
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1answer
29 views

Can you implement Replay Buffers for Reinforcement Learning when most experiences give zero reward?

Specifically, for a deep deterministic policy gradient, DDPG, to expedite the learning speed, it's recommended to use a Replay Buffer What if the reward is only given at a terminal state? Or, most of ...
2
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1answer
82 views

Define statistical potential energy [closed]

I am looking for a statistical method that closely relates to the idea of potential energy. Here is a quick google definition for potential energy "...the energy possessed by a body by virtue of ...
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0answers
8 views

Extracting regimes from a time series

Trying to find a good way to solve the following problem: I have daily time series $\{x_n\},$ say for the last 10 years. During that time span there are several shorter periods (say, Dec '12 - April '...
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0answers
19 views

Discussion on building logic for Churn for monthly renewal [closed]

I have a subscription based business dataset which looks like this: ...
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1answer
27 views

Removing noise with Variational Autoencoders

I have one question that is related to variational autoencoders: can they be used as a denosing algorithm in the same way as standard denosing autoencoders? I generally see people removing the ...
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0answers
17 views

temporal autocorrelation machine learning algorithms

I am trying find out the relationships of stream integrity against Land uses. I have 4-years of stream integrity data (1998-1999, 2004, 2009, 2014) and corresponding land use data of 1995, 2002, 2007, ...
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0answers
12 views

how to deal with dependent variables as a list of integers in machine learning

In my working project, I'm building machine learning models to predict number of hospital admissions from patient profile. The dependent variable, # of hospital admission are integers from 0 to 8. ...
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2answers
31 views

Evaluating Classifiers k fold CV or ROC

I've been doing a project to determine the 'best' classifier for classification on a dataset from UCI. I used 10 fold stratified cross validation to calculate the mean accuracy. However it was ...
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2answers
58 views

on-line regression with 1 output [closed]

I have 12 input variables from sensor (IMU) to predict 1 output (Speed of a boat) variable. Is it possible to use regression (or something else?) in this case where it is a continuous data stream from ...
1
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1answer
9 views

Good way to use word similarity as a feature in supervised ML on text

I have a pretty low N data set of small sentences tagged with a label. I would like to create a classifier on this dataset. The word choice is not very variable since the domain is pretty specific. ...