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1500 questions
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4 answers

Exploratory Data Analysis with Image Datset

In Machine Learning Kernels on Kaggle I often see EDAs with structured data. So, I was wondering, if there are any recommended/standard procedures for EDA with image datasets. What kind of statistical analyses do you conduct, what kind of plots do…
sushipositive
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what machine/deep learning/ nlp techniques are used to classify a given words as name, mobile number, address, email, state, county, city etc

I am trying to generate an intelligent model which can scan a set of words or strings and classify them as names, mobile numbers, addresses, cities, states, countries and other entities using machine learning or deep learning. I had searched for…
Sai Charan Adurthi
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Confusion Matrix - Get Items FP/FN/TP/TN - Python

After run my python code: print(confusion_matrix(x_test, x_pred)) I get this: [100 32 211 21] My question is how can I get the following list: True positive = 100 False positive = 32 False negative = 211 True negative = 21 Is this possible?
John_Rodgers
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LSTM: How to deal with nonstationarity when predicting a time series

I want to do one-step-ahead predictions for time series with LSTM. To understand the algorithm, I built myself a toy example: A simple autocorrelated process. def my_process(n, p, drift=0, displacement=0): x = np.zeros(n) for i in range(1,…
Elias Strehle
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2 answers

Always drop the first column after performing One Hot Encoding?

Since one of the columns can be generated completely from the others, and hence retaining this extra column does not add any new information for the modelling process, would it be good practice to always drop the first column after performing One…
Gale
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Convolutional Neural Networks layer sizes

I am trying to understand an article Backpropagation In Convolutional Neural Networks But I can not wrap my head around that diagram: The first layer has 3 feature maps with dimensions 32x32. The second layer has 32 feature maps with dimensions…
koryakinp
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Imbalanced data causing mis-classification on multiclass dataset

I am working on text classification where I have 39 categories/classes and 8.5 million records. (In future data and categories will increase). Structure or format of my data is as…
outlier
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LSTM Feature selection process

We need to implement a time series problem with the LSTM model. But, while implementing the same, the main challenge I am facing is the feature selection issue. Because our data-set contains 2300 observations and 600 features. And we already know…
Abhishek Saha
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9
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2 answers

Understanding the mathematics of AdaGrad and AdaDelta

I have been building some models for a project, but I can't wrap my head around the math of Adagrad and Adadelta algorithms. I do understand how vanilla gradient descent works and I have written code for making it work successfully. I will be…
Malay Hazarika
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Which algorithm to apply for choosing the right point

Picture below shows 7 points around the origin. One of them has been selected by a human based on rules and experience and is colored red (the one in the lower left quadrant). Now we have over 1000 of these sets of points and for each set a human…
Elmex80s
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How to train data by batch from disk?

I am working on a convolutional neural network for image classification. The training dataset is too large to be loaded on my computer memory (4gb), on top of that I also need to try some augmentation to balance the classes. I am using keras. I have…
Learning is a mess
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Python : Feature Matching + Homography to find Multiple Objects

I'm trying to use OpenCV via Python to find multiple objects in a train image and match it with the key points detected from a query image. For my case, I'm trying to detect the tennis courts in the image provided below. I looked at the online…
Reward
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4 answers

How to get predicted class labels in convolution neural network?

I have built a convolutional neural network which is needed to classify the test data into either 0 or 1. I am training the CNN with labels either 0 or 1 but while running the below code I am getting the following result. predictions =…
LIsa
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Input for LSTM for financial time series directional prediction

I'm working on using an LSTM to predict the direction of the market for the next day. My question concerns the input for the LSTM. My data is a financial time series $x_1 \ldots x_t$ where each $x_i$ represents a vector of features for day $i$, i.e…
articuno
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Using NLP to automate the categorization of user description

I have a huge file of customer complaints about the products my company owns and I would like to do a data analysis on those descriptions and tag a category to each of them. For example: I need to figure out the number of complaints on Software and…
SRS
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