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K-means++ cosine distance

I am wondering how to implement k-means++ with cosine distance, acording to quote below (wikipedia), which says, that distance needs to be squared. But with square is lost direction of distance. ...
5 views

How is it possible (if at all) to implement additional business constraints to an ensemble machine learning model, such as random forests or boosted trees? These additional business rules can be ...
3 views

TSNE parameters

Trying to tune the parameters of sklearn.manifold.TSNE(n_components=2, *, perplexity=30.0, early_exaggeration=12.0, learning_rate=200.0, n_iter=1000, n_iter_without_progress=300, min_grad_norm=1e-07, ...
8 views

How to extract features insights to change classifier decision?

I don't know if my question is specific enough but there's what I mean. Suppose we have high school grades of students who attended a Computer Science degree and whether or not they succeeded (given a ...
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Phrase/Token labeling

Looking for suggestions on how to define the following NLP problem and different ways in which it can be modeled to leverage machine learning. I believe there are multiple ways to model this problem. ...
8 views

Testing of hypothesis - Which algorithm is best?

In my case, I have run 2 Algorithms with lstm (rnn) but with different loss functions on the same sample. I have to test whether which algorithm (loss function) works better than the other. For both ...
5 views

How to inference of time series with RNN(like LSTM, GRU etc)

Say I am doing a time series prediction which predict some value for next time step with past T inputs from historical inputs. Say I am using a RNN module like LSTM or GRU. In trainning/validation, I ...
6 views

Why concatenating these layers, why applying masks over and over to partial convoluted image?

I have to ask some questions about one topic. In this sentence of Nvidia's article of : https://arxiv.org/abs/1804.07723 , they are saying:"The last partial convolution layer’s input will ...
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Having issues with DataSet

I just started learning data science and am having a problem when generating a dataset. Dataset: ...
3 views

Error while calculating accuracy and matrix multiplication in tensor flow code for regression

I was writing a code for linear regression using tensor flow but I was getting errors while calculating matrix multiplication using tensor flow and while calculating accuracy. ...
9 views

How to feed the model with a stack of images instead of one by one?

I built a 2D model, but the dataset contains a group of images from different viewpoints for each patient, so the input should be a stack of images for each patient. I have compressed each group of ...
11 views

Deep Learning with Time Series Data (containing Log Returns)

I am curious about how I would begin to approach this problem. I am working with a time series multi-indexed data frame (consisting of precomputed log returns) of various stocks. In this dataframe, ...
12 views

How to calculate accuracy for regression using tensor flow [closed]

I was trying to run this code but I was getting some errors. I looked at the code thoroughly, but it appears correct. but I was getting errors at matrix multiplication and accuracy. ...
15 views

How much data augmentation is required on an imbalanced dataset?

Imagine I have a dataset with positive and negative sentences, and I need to train a transformer (Like BERT) to do the binary classification. The problem is that there are 100 negative sentences and ...
17 views

Matrix multiplication using tensor flow

I am trying to run this code for linear regression using Tensor Flow. I have to use Tensor Flow matrix multiplication, but I am getting errors. My code: ...
6 views

Clustering: How to find which point in a cluster in the closest to the cluster centroid while using kprototype

I have a dataset which contains both numeric and categorical data. In order to carry out clustering in python I have applied kprototype which is the mixed form of kmeans to be used in such cases. I ...
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Find if a string appear before another string [closed]

I have a string variable containing patients' addresses. My goal is to flag patients who live in "401 30th street". I would like to flags strings that contain the number "401" ...
24 views

How to stay up to date in NLP and use the best approaches?

There are many fast advancements in NLP field, BERT, RoBERTa, ALBERT, and XLNe, and no one can check the news or papers daily. Is there any way or site that keeps track of all these new developments ...
9 views

Classification of RGB images

What is the preferred way to specify the features for image classification when the input consists of RGB images? Is it a good approach to flatten the image into a single vector (where for instance '...
5 views

Continuous Bag of Words loss function and training objective

CBOW from what I understand, obtains a probability distribution $P(w|c)$ for all words $w$ in the vocabulary, given context $c$. Th loss function is: $-logP(w|c)$, which means this would be maximised ...
11 views

Trouble with anomaly/novelty detection (on microscale) - need easy practical guide with Keras

I am relatively new to the field of machine learning. However, I already have solved simple image classification tasks with Keras (for example building CNNs and classifying MNIST...). The rough deep ...
35 views

Understanding SVM mathematics

I was referring SVM section of Andrew Ng's course notes for Stanford CS229 Machine Learning course. On pages 14 and 15, he says: Consider the picture below: How can we find the value of \$\gamma^{(i)}...
15 views

For sklearn ML algorithms, is it possible to use boolean data alongside continuous data for the predictive data, and if so how can the data be scaled?

I have a medium size data set (7K) of patient age, sex, and pre-existing conditions. Age of course is from 0-101, sex is 1 for male, 2 for female, and -1 for diverse. All the pre-conditions are ...
24 views

Binary classification with imbalanced dataset, about lightgbm output probability distribution

I trained a binary classifier for an imbalanced dataset. I did two experiments: lightgbm classifier, boosting_type='gbdt', objective='cross_entropy', SMOTE upsample After training the lgbm model, I ...
20 views

Reinforcement Learning, wont learn and bad in test set

I'm study and try to understand better the reinforcement learning branch; In this case I want to learn the agent to make a reward; I've tried with: A2C DQN PPO2 but the agent in test env make ever ...
102 views

How to perform text classification on a dataset with many imbalanced classes

I am completely new to NLP and I have been tasked with performing text classification on a dataset containing 193k records. The number of classes is 107. The class with the highest number of records ...
19 views

Developing a deep learning hybrid architecture for a particular problem is a highly complicated task [closed]

I am currently conducting research on application of deep learning (sensor signal recognition). I spent about a year and a half sifting through the literature and discovered some research patterns. To ...