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Questions tagged [probability]

Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur or how likely it is that a proposition is true.

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2answers
131 views

How to model user choice probability: binary model vs multi class model

Let's say Morpheus has multiple users to offer colored pills(from an infinite set of colored pills), there are in total 3 unique colored pills(red, blue, green) Morpheus can offer. The trick is, ...
2
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1answer
82 views

why does my calibration curve for platts and isotonic have less points than my uncalibrated model?

i train a model using grid search then i use the best parameters from this to define my chosen model. ...
1
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1answer
27 views

What probability distribution would be more appropriate for monthly rate of going to the store?

Part of a model I am making includes the frequency with which people go shopping for a given good (e.g. people on average go to the supermarket some n times a month). I am trying to figure out what ...
2
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2answers
47 views

how classification scores are interpreted?

I would like to know how to interpret classification scores (i am not sure about the word score or probability, please correct me). For example, for a binary classification positive values are ...
2
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1answer
74 views

Stacked Model performance?

I am currently working with a dataset that seems very easily separable and I have an accuracy of 99% for SVM (NN-98%, RF-98%, DT-96-97% and I have checked for leakage & overfitting). As part of my ...
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0answers
19 views

using logistic:binary as objective in xgboost

i am using 'binary:logisitic' as my objective function in xgboost classifier. Therefore when i predict probabilities i.e: model.predict_proba(x_test)[:, 1] will ...
1
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2answers
63 views

Lower loss always better for Probabilistic loss functions?

I am working on an neural net int Tensorflow that predicts percentages for win, draw, loss for given data of a game. The labels I provide are always {1, 0, 0}, {0, 1, 0} or {0, 0, 1}. After some ...
2
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0answers
75 views

how can i plot probability distribution of my classes in the way below?

All, I would like to plot the following: I have a binary classification problem where I am using xgboost as my 'model' below: ...
0
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1answer
19 views

how can i interpret kernel density plots from classification?

all, i have a classification problem where i am predicting likelihood of client defaulting on loan. i plotted the predicted probabilities from my model, and then plotted against the label '1' for ...
0
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0answers
73 views

Evaluation of Mixture Density Networks

I have programmed an Mixture Density Network model to a market price. As input I have many numerical and categorical properties. The output of the network is a probability distribution (shape, ...
1
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1answer
268 views

Understanding output probabilites of xgboost in multiclass problems

I would like to understand the output probabilities of a xgboost classifier (or any other decision tree ensemble based classifier) in the case of a multiclass problem. For example: We have 5 different ...
1
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1answer
75 views

Probability of Gaussian Naive Bayes

How would I go about attaching a probability to the prediction outputted by a Gaussian Naive Bayes model ? I'm asking because the predict_proba function U can use with sklearn's Gaussian Naive Bayes ...
2
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2answers
62 views

Notation for features (general notation for continuous and discrete random variables)

I'm looking for the right notation for features from different types. Let us say that my samples as $m$ features that can be modeled with $X_1,...,X_m$. The features Don't share the same distribution (...
1
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1answer
574 views

What is the concept of Normalized Mutual Information in the evaluation of Clustering?

I know what mutual information basically is but not quite sure about why and how it is used in the context of evaluation of clustering mechanisms ? Can someone please explain the intuition behind it ? ...
0
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1answer
24 views

Finding gender affinity for businesses

What are the different models I can use to find the gender affinity of businesses using yelp dataset-- https://www.kaggle.com/yelp-dataset/yelp-dataset . I need to find Probablity (Male buying from a ...
1
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0answers
22 views

How do data scientists reason under ambiguity? [closed]

I am looking for real-wrold examples of how data scientists build models and make decisions under situations of extreme ambiguity as described by Cassie Kozyrkov here: A decision under ambiguity ...
0
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1answer
684 views

Fitting a pandas dataframe to a Poisson Distribution

I have a simple dataframe df2 that consist of indices and one column of values. I want to fit this dataframe to a poisson distribution. Below is the code I am using: ...
1
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1answer
179 views

how to compute bernoulli entropy?

I am reading gail implementation code in openai baselines. they compute bernoulli entropy as one of the loss in adversary network loss function. In their code, they implement bernoulli entropy as ...
2
votes
2answers
207 views

why we sample when predicting with Recurent Neural Network

I trained a Recurrent Neural Network to predict the next word in a sentence. I trained and now I want to predict, but there is something I am not getting well. I saw it in many tutorials even in the ...
1
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0answers
36 views

Ranking graph's nodes by score propagation

Problem I have the following directed tripartite graph $G(E\cup V\cup P, A)$, where there is a many-to-one symmetric relationship between the subsets V and E - $e\in E,v\in V,[e, v]\in A \iff [v, e]\...
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0answers
36 views

“Smearing” probabilities or how to handle imprecise locations for canonically classification-type problems

I am trying to predict failures at different nodes on a line. Each node has different weather features and hardware/configuration features. For a little under half of the historical failures I have, I ...
1
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2answers
28 views

Calculate probability in a dataset

What is a good way to calculate probabilities in a dataset of samples? Each sample is a measurement, that is usually 1 or 0. The goal is to calculate probabilities based on all feature rows. Simple ...
1
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1answer
52 views

Clarifying Probability Mass Function (PMF)

I am currently reading Deep Learning book, and I want to get better understanding of probability theory. In chapter 3.3.1 of Deep Learning book it states that: Often we associate each random ...
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1answer
26 views

How to perform link prediction in text based relationship data

I need to establish if there is a link between 2 columns from two different datasets with one matching column, where; ...
2
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1answer
142 views

Convolution and Pooling as Infinitely strong priors

I am currently reading about Convolutional Neural Networks in Deep Learning Book. I am stuck on section 9.4 titled "Convolution and Pooling as Infinitely String Priors". Could someone please ...
0
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1answer
390 views

How to compute denominator in Naive Bayes?

Suppose we have class C_k and input feature vector x in dataset How to calculate probability ...
2
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0answers
24 views

Practical example and working of Laplace Smoothing or Linear Interpolation in Natural Language Processing (NLP)

Let us suppose we have a document where total_words = 50 (for example -> is,the,now,is,am,here,now) total_unique_words = 40 (for example -> is,the,am,here,now) How can we apply the ...
1
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1answer
18 views

Understanding these probabilities, and reading the pdf and cdf

UPDATE: this is a math question but as i would like to codify it, I thought the DS SE might be appropriate. I am trying to sketch out this problem statement. Where am I going wrong since I don't see ...
2
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0answers
30 views

overlapping of surfaces with holes

I have two disks, of equal diameter. Both disks have a 'spatter' of holes, in random positions (from a two-dimensional - i.e., surface - uniform distribution; in other words, holes close to the sides ...
2
votes
1answer
31 views

Control which features are used for every task in multioutput classification?

I would like to perform a multiclass-multioutput classification task, on vectorized textual data. I started by using a random forest classifier in a multioutput startegy: ...
2
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1answer
78 views

why naive is needed in Naive Bayes ,what happens if naive is not included in Bayes theorem?

Im trying to understand why naive is needed in Naive Bayes and everyone says Naive Bayes assumes the input features (predictors) are not correlated hence they are not dependent on each other . i want ...
2
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0answers
15 views

Connection between prob output LogisticReg/SVM and ROC

I have the following ROC generated using LPOCV and Logistic regression or SVM (l2 norm). Now, let's say I have a test set containing 10 patients and I get that the probabilities of those patients to ...
0
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1answer
30 views

What is the name of this statistical interaction?

What is the name of the following statistical / informational interaction: given A, I know exactly what B is. given B, I know to some extent what A is. I'm not looking for a probability but rather ...
1
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1answer
2k views

XGBoost: How to set the probability threshold for multi class classification

I am using the XGBoost for classification of text data. There are the 3 different classes in the training dataset. ...
0
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1answer
40 views

How to interpret axis of Histogram and distribution curve?

After doing statistical analysis of data I got the below figures: The data contains a line length in meters which is represented with Line(m). The purpose here is to confirm the distribution behavior ...
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0answers
18 views

How does one use activation function with greater than [-1;1] range for binary classification?

In Efficient Backprop (http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf), Lecun and others propose to use activation function that don't reach target values on their asypmptotes. They explain (§ 4....
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1answer
22 views

Rules/Methods to use for determining user groups with no review data

I’m working on an analytical problem where I have customers who deal with end consumers. End consumers can leave customers reviews based on their experience (Star ratings, text etc). I’m trying to ...
1
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0answers
41 views

Calculate marginal probability distributions of a dataset

I have a dataset with 'n' features and a label(binary) corresponding each entry. I am using a predicitive model to predict these labels using those 'n' features. Now, I wish to know the marginal ...
3
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1answer
376 views

Confidence value for face recognition

In the context of face recognition I have the following histogram: blue bins count the comparison distances for "self matches" (comparing two images of the same person). Orange bins count the ...
2
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1answer
34 views

Synthetic time series generation according to some distribution

I'm trying to develop a change detection model that uses sliding windows. Given a time series with some features I've a sliding widows that analyses that time period and compares with a successive ...
2
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0answers
53 views

Difference between Gibbs sampling and variational Bayes inference

After reading in blogs and books, I came to the conclusion that Gibbs sampling and variation Bayes are methods for estimating or inference of posterior. Below link described but it's difficult to ...
3
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1answer
284 views

Re-sampling of a Histograms Bins

I would like to be able to resample a histograms bins without having access tot he raw data. And just to be clear, by resample, I mean to change the number of bins and still provide a good estimate ...
3
votes
3answers
339 views

What is the meaning of likelihood?

I am studying Bayes probability applied to machine learning, and I have encoutered the concept of likelihood, which I don't understand. I have seen that the Bayes rule is: $P(A|B)=\frac{P(B|A)P(A)}{...
-1
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1answer
563 views

Implementation explanation for predict_proba in RandomForestClassifier- sklearn

Attached is an extract from the RandomForestClassifier documentation of sklearn. The last line,"The class probabilities of a single tree is the fraction of samples of the same class in a leaf." is ...
2
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1answer
414 views

Predict_proba() probabilities distribution [closed]

I’m trying to calculate probability of class 1. I’m using gradients boosting (catboost classifier) Is it normal to have an equal rate of positive classes in every predict_proba() bucket? e.g.: [...
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0answers
18 views

Is using cross-entropy enough to ensure the output is a distribution probability?

I am following along https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html. In this code, the last layers of the pretrained networks are linear. The loss used in this ...
1
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1answer
291 views

Adjust predicted probability after smote

i have an imbalance data set and I used smote to oversample the minority class and undersample the majority class. now, I want to check the test AUC using predict_proba of the model. I have two ...
0
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0answers
126 views

Statistical loss function for categorical distributions

For training an autoencoder model whose outputs (and inputs) are parameters from a categorical distribution $[q_1, q_2, \ldots, q_n]$, I have to define a proper loss function measuring the distance ...
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0answers
35 views

Why Maximum Likelihood Estimation for normal distribution?

Since we can compute the mean and the standard deviation of a set of random variables, why do we use Maximum Likelihood Estimation to estimate these parameters?
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2answers
73 views

What is the meaning of “probability distribution of p(x)” of something uncountable?

I'm studying VAE and new to both of the neural network and the statistic. After some researches, I could understand the rough concept of VAE. But what makes me confused is, the meaning of probability ...