Questions tagged [numpy]

NumPy is the fundamental package for scientific computing with Python.

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27 views

How to approximate a function using Fast Fourier Transform? [closed]

I'm trying to approximate a complex function (I have millions of points to sample) using Fourier transform. I used Legendre and Chebyshev polynomials to approximate it before, and it worked pretty ...
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0answers
12 views

time complexity of sampling from multivariate hypergeometric distribuiton

numpy has an implementation and the doc is here. It says it is "roughly" equivalent to: ...
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2answers
35 views

Violin plot of 2 numpy arrays with seaborn

I would like to compare the distribution of 2 numpy arrays using a violin plot made with seaborn. The maximal value in both arrays is 1. The plot suggests a higher maximum. Am I misunderstanding the ...
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0answers
33 views

Neural network from scratch: only predicts training inputs correctly [duplicate]

Here is a neural network I've been working on. It takes in an array of four zeros or ones and predicts whether that pattern of zeros and ones is a backslash. ...
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22 views

Predicting new values after feature scaling

I am trying to do linear regression with one feature only: predicting height with weights. Gradient descent took too many epochs so I used a min max scaler and it converged to the optimum point pretty ...
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0answers
64 views

Basic RNN sequence classifier diagram?

I'd like to build an RNN in numpy from scratch to really get come comfortable with backpropagation through time (BPTT.) In the below diagram and LaTeX, I show two neurons, each with a non-linearity, N(...
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2answers
50 views

Why sampling different random variables sequencially using the same PRNG alters the sequence that would be obtained if only one was sampled?

When using random variables in most programming languages the usual process is based on instatiating a RandomGenerator which will output an stream of pseudo-random numbers and with this stream the ...
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0answers
21 views

entropically regularized optimal transport on matrix with zero's on diagonal

I am a student reading an article where they are using the sinkhorn function from the ot Pyhton package to calculate the ...
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0answers
5 views

How to check the level against target encoding in my numpy array for the target feature?

I have a target variable called population that i first discretized using qcut with equal width binning , This gave me a single column df with 235 rows for the various countries ...
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5answers
22 views

Neural network based on twitter followers, what would be my features?

I was thinking of training a neural network that would be able to classify twitter users according to their followers. For example, I would like to know if a user is "gamer" or not by the people they ...
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1answer
106 views

representing quantile like quartile in form of normal distribution curve

I learned in statistics the first quartile, 2nd quartile, and 3rd quartile can be represented in the figure1 below I came across this part of the article Step 4 - Feature Engineering.In this portion ...
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1answer
78 views

How to plot the prior, posterior and likelihood function from given data in python [closed]

I wrote a simple bayesian program which calculates prior, posterior and likelihood in python. ...
2
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1answer
30 views

Does normalization also help to prevend the vanish/exploding gradients?

I am implementing my own neural network from scratch using numpy. I tested my code with the MNIST dataset and I forgot to normalize the images and my code did not work, because I got an error about a ...
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23 views

What is the difference between np.linalg.norm(x-y,axis=1) and np.linalg.norm(x-y)?

I'm creating a K-Medoids algorithm from scratch in Python using numpy, and I'm in the process of using a distance function to determine the cluster center. I want the center to be the point in the ...
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1answer
32 views

How to make predictions with libmf using python? [closed]

I'm trying to implement libmf library in python. I tried with the following example: ...
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1answer
14 views

Stnadard deviation of values containing different ranges

Taking the $\sigma$ of these values : np.std([55,50,40,45]) returns: 5.59 If I take the $\sigma$ of these values: ...
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0answers
13 views

Simple ANN model converges with tanh(x) as the activation function, but it doesn't with leaky ReLu

I'm training a simple ANN model (MLP) using as the activation function tanh(x) and, after some interactions, it converges with error equal to 10^-5, here's my full ...
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0answers
15 views

Weights between the Last 2 layers keep getting negative

TL;DR weights between the last 2 layers keep getting negative to the point that the softmax(z) of the output layer can't divide by zero ( e^-750 ~= 0 thus deciding by 0) I am making a Neural Network ...
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1answer
74 views

How to get the variance between two arrays?

import numpy as np a = np.array([[1,2,4],[2,4,8]]) np.var(a) output: 5.25 Can anyone enlight me what's the calculation process to get variance = 5.25?
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32 views

Finding weight value for smooth constrained least squares that comes closest with a priori solution?

I need to solve a system of $n.k$ equations of form $t_{ij} = a_i + b_j + x_{ij}/v$, with $i = 1, ..., n$ and $j = 1, ..., k$. A least squares approach can be used, as in $d = Gm$. My data is $t_{ij}$...
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13 views

Gaussian mixture models for image matrix not determining E step

I want to calculate responsibility for each of the data points, for the given MU, SIGMA and PI. ...
2
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1answer
124 views

Interpreting scipy.stats: ks_2samp and mannwhitneyu give conflicting results

I've encountered conflicting results between ks_2samp and mannwhitneyu while trying to compare two empirical distributions, ...
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0answers
72 views

Combine TFIDF with non-textual features

I am dealing with an email classification problem in which I have email requests coming from different groups of people. I am building a classifier to classify these emails based on historical email ...
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0answers
37 views

Estimate joint probability of two dependent variable

I've a dataset created in the following way: The input of the system is a 8 bit binary number ranging from $x_1$= 0000 0000 to $x_N$ = 1111 1111 For every input i've read the output of the system (...
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0answers
77 views

Generate random values to mimic skewness

I have a actual set of data where the variables are heavily skewed, both positively and negatively. I need to generate random sample data for the values going forward. The data needs to be similarly ...
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0answers
54 views

Q-Exponential distribution in Numpy

I am studying a phenomena, which I know is characterised by the q-exponential distribution, with parameters $c=1$, $q = 1.355$ and $b = 0.524$ in the equation $$e_{q,b,c}(t) = c(1 + b(q-1)t)^{\frac{1}{...
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18 views

Adding features lowered accuracy score Gaussian Naive Bayes algorithm, Python

I am in third year of university, this simple py program is meant to use the Gaussian Naive Bayes algorithm to create a model and evaluate it. ...
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1answer
22 views

Feeding multiple rows of data into ANN [closed]

I've built an ANN from scratch, that works with one row of data with any number of neurons and hidden layers. For the setup I am using 2 hidden layers, 5 neurons (just while building). The network ...
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0answers
72 views

Infinitesimal generator of Markov chain using numpy

I am computing the infinitesimal generator of a continuous-time Markov chain from the transition probabilities p. I am following the methodology described here, ...
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2answers
322 views

Transforming data for normality with negative values using python

I am working with a data set in a machine learning project, which has lots to negative values. I want to transform the distribution of my data to normal. I tried using numpy.log, but since log is only ...
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0answers
45 views

Numpy corrcoef giving different result from manual calculation

I'm trying to calculate a partial correlation matrix for a high dimensional problem. I'm using this paper as a guide. I'm also referencing this function from Pingouin. Starting from the inverse ...
2
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0answers
16 views

Can't Recreate Values for U, S, V from SVD in numpy [duplicate]

To better understand SVD, I'm trying to recreate the values for U, S, and V using straight ...
4
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1answer
208 views

QR Factorization to Solve Least Squares Without Using an Inverse

I'm playing around with different ways to solve least squares, and am using numpy to derive values for $\beta$ in a regression problem. I know that if you do a $QR$ factorization of $X$ such that $...
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0answers
27 views

Dataframe containing value 0 should be removed or replaced?

I have a question that mostly I get stuck at. I was looking at the data for diabetes patients and found that most of the rows have 0 values under most of their columns. Reference for the url https://...
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1answer
274 views

KL Divergence of two standard normal arrays

I generated two 9000,1 np arrays with a = np.random.standard_normal(9000) b = np.random.standard_normal(9000) Then I check the KL Divergence with ...
3
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0answers
181 views

James Stein Estimator for more than one Sample

I have a hard time understanding the James-Stein Estimator. I show you how I tried to comprehend it by using a python example. I take a normally distributed random vector with mean $(0.1, 0.2, 0.3, 0....
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1answer
106 views

Outliers of small dataset

I have a python function that takes a list of smaller images boxes (represented as float arrays) and the whole image img in as a ...
1
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1answer
654 views

Fitting Beta Distributions to Data

I am trying to reproduce some beta distribution parameters found in this published paper. I have two data sets, y1 and y2, that ...
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0answers
20 views

Proper way of calculating statistics for samples probabilites [closed]

I have 64 samples and for each one of them, I have their probability. I was wondering which is the correct way to find a mean and std for the above-mentioned population. If I do something like: <...
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0answers
174 views

Gradient Descent Vectorization with Numpy (1D transpose confusion) [closed]

I'm working through Andrew Ng's original Stanford course and ran into some numpy confusion. Basically, my main question is, if we dot product a 1D array with a 2D array in numpy (and the dimensions ...
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0answers
26 views

is it reasonable to consider a plot of 2 separate normal random variables as the geometric representation of a joint probability distribution?

I am plotting 2 normal distribution in Python. if anyone could provide an R version to demonstrate and explain, that would be grateful. ...
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1answer
3k views

Array of samples from multivariate gaussian distribution Python

I am trying to build in Python the scatter plot in part 2 of Elements of Statistical Learning. First it is said to generate 10 means mk from a bivariate Gaussian distribution N((1,0)T,I) and ...
2
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1answer
312 views

Efficiently Computing The Beta CDF [duplicate]

I am using numba to JIT compile some looped python functions as part of a larger application. Ideally, everything will run in numba's "no python" mode, such that the loop can be parallelised. One of ...
2
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1answer
1k views

Ridge Regression with Gradient Descent Converges to OLS estimates

I'm implementing a homespun version of Ridge Regression with gradient descent, and to my surprise it always converges to the same answers as OLS, not the closed form of Ridge Regression. This is ...
3
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1answer
785 views

Implementing Lasso Regression in Numpy

I'm doing a little self study project, and am trying to implement OLS, Ridge, and Lasso regression from scratch using just Numpy, and am having problems getting this to work with Lasso regression. ...
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0answers
47 views

Rank 1 SVD with constraint on U

I need to perform a particular rank 1 decomposition of a sparse matrix $\mathbf{A} \in \mathbb{R}^{n\times n}$. In particular I am looking for the positive vector $\mathbf{u} \in \mathbb{R}^{+n}$ ...
0
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1answer
76 views

What is the formula for calculation of `R_ij` in `numpy.corrcoef(x, y, rowvar = False)`?

The manual does not provide the formula if we pass x and y. I do not understand the matrix I get. Here is my code: ...
1
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1answer
23 views

Memory considerations with sklearn classfier

I am trying to fit a sklearn.ensemble.RandomForestClassifier. The [docs] explain that a matrix (rows - observations, columns - features). My observations are 700 ...
3
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1answer
3k views

PCA principal components in sklearn not matching eigen-vectors of covariance calculated by numpy

I was trying to replicate PCA in sklearn's PCA API using numpy using PCA in numpy and sklearn produces different results. I noticed that: eigenvalues are same as the PCA object's explained_variance_ ...