All Questions
35,912
questions
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Perhitungan LDA
pertanyaan saya : apakah ada yang sudah pernah melakukan perhitungan LDA secara manual? saya mengalami kesulitan dalam perhitungan manualnya
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4
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Selecting an element in a sequence with self-attention networks
I have a doubt on I should set up the following problem:
Data:
My data is a tensor with shape (N, J, F) where N is the batch size, J is the sequence length, and F is the number of features of each ...
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5
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Faster R-CNN: are the proposal coordinates predicted in stage 1 fed as input to the bbox regressor of stage 2?
If I understand correctly, stage 2 of Faster R-CNN "refines" the proposals predicted by stage 1. However, this would require providing the coordinates from stage 1 as input to the bbox ...
- 347
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6
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Implementing a dataset to Computer Vision Article
I want to implement the PIE dataset in the AgentFormer arch.
AgentFormer uses ETH and nuScene datasets. I successfully run these datasets on this arch. However, I couldn't take a good way with the PIE ...
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6
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the accuracy of a random baseline
Hi everyone I am new in machine learning and deep learning field can someone explaining to me, What is the accuracy of a random baseline ?
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1
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24
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Is there a machine learning model I should look into to predict the effect land topology will have on prevailing wind direction near bodies of water
I'd like to predict the change in wind velocity due to land near bodies of water. Warmer or colder land should change the wind velocity of nearshore breeze. I'd also like to predict wind shadows that ...
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5
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When evaluating an ML model, does it usually occure that some changes on the data should be made? made some changes,but not sure, if its correct to do [closed]
from sklearn.metrics import accuracy_score, precision_score, f1_score
import numpy as np
from tensorflow import keras
outs_all_flat = outs_all.reshape((71716*60,))
words_all_flat = words_all.reshape((...
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7
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find the parameter that minimize a multivariate distribution
i was trying to use scipy's minimize scalar to find the value of the parameter T that minimize the negative log-likelihood of a multivariate distribution with covariance matrix C. if i understood ...
- 101
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6
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Install package from conda-forge
I am trying to install the TRIQS package from conda-forge. As mentioned here, I used conda install -c conda-forge triqs on ...
- 101
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1
answer
13
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How do GPT models go from token probabilities to textual outputs?
Suppose GPT-2 or GPT-3 is trying to generate the next token, and it has a probability distribution (after applying softmax to some output logits) for the different possible next tokens. How does it ...
- 101
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votes
2
answers
17
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Why is cycle consistency loss alone not sufficient to produce meaningful output?
Imagine an adaptation of CycleGAN, in which the discriminators were removed in lieu of using only cycle consistency loss. Well, it turns out that the original authors of Cycle Consistent Adversarial ...
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1
answer
14
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Is there a standard order of operations for data preparation?
In what order should I do the following given a dataset:
(E)ncoding of Categorical Variables
(N)ormalization
(B)alancing of data
(I)mputation of Missing Values
(R)emoval of Duplicates/Infinity/...
- 15
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13
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Do you have to use clustering with SciKit-Learn's Mutual Information metric?
I'd like to calculate the mutual information between two datasets, but I'd prefer not to cluster them first.
I'm thinking of using SciKit-Learn's mutual_info_score ...
- 511
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1
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10
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Single model or multiple models for predicting at each level in a multi-level classification problem
Given a flat structured data with features that can be considered hierarchical, where each feature is at a different level (e.g., Brand at the top level, Product, Color, and Size at different levels), ...
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11
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Accelerated learning when wrapping layers in a class
I am implementing a VGG-like network using Pytorch 1.13.1 (python=3.7.12) for image classification on the CINIC-10 dataset. The following two implementations turn out to have very different training ...
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7
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how to define search space over hyperparameters automatically?
I'm trying to automate retrain steps of our ML models. My aim is hyper-parameter tuning with current data (newer performance window) using same algorithm and features on production environment. ...
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1
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I used SMOTE-ENN to balance my dataset and it improved the performance metrics, but how can I be sure it's not overfitting?
The models were evaluated using 10-fold cross validation.
foldCount = StratifiedKFold(10, shuffle=True, random_state=1)
The models in question are XGBoost.
...
- 15
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1
answer
14
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How many parameters does the vanilla Transformer have?
The original Transformer paper (Vaswani et al; 2017 NeurIPS) describes the model architecture and the hyperparameters in quite some detail, but it misses to provide the exact (or even rough) model ...
- 163
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4
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Couldn't get the correct values after denormalizing LSTM Model
I couldn't get the correct value of the actual stock price after I denormalized the prediction value. The actual stock price should be around 150+-, however, after denormalizing it only shows around ...
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3
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Optuina pruning during CrossValidation, does it make sense?
I'm currently trying to build a model using CatBoost. For my parameter tuning, I'm using optuna and cross-validation and pruning the trial checking on the intermediate cross-validation scores. Here ...
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2
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29
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How to boost the performance of a single decision tree by adding additional trees?
I have a binary classification task and the data has imbalance issue (99% is negative and 1% is positive). I am able to build a decision tree that is carefully tuned, weighted, and post-pruned. Take ...
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15
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how each tree in random forest structured/built?
I'm new to machine learning and I want to use random forest for the problem I have. What I have done so far is I did the 80/20 split of the original data set.
I need to understand what will happen ...
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15
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GitHub Archived Repositories
I'm trying to build a model that observes patterns of source control usage, from how many files are changed per commit, how many contributors there are, even semantic analysis on the commit messages.
...
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10
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How to fit datasets accounting for standard deviation in Python?
I have multiple datasets of measurements with standard deviation and I would like to fit all the data (with a non-linear regression model) accounting for SD or SEM (it is quite similar to let the ...
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5
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fine tuning open ai model with historical data
i'm trying to understand more about training models and unsure how to approach this problem.
I have a bunch of historical financial data that I would like open ai to use as additional context when ...
- 101
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1
answer
12
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moments of weight vectors in Adam
When performing backpropagation with Adam algorithm, are the moment and the second moment of the weight vectors calculated also for the weights in hidden layers?
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11
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Where can I find gpt-35-turbo in the Microsoft Pricing calculator?
Where can I find gpt-35-turbo in the Microsoft Pricing calculator? I don't see gpt-35-turbo in the model list:
https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/ ...
- 5,478
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6
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Feature selection in high-dimensional datasets with sparse features
What are the most effective techniques for feature selection in high-dimensional datasets with sparse features in the field of natural language processing?
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9
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Word2Vec Data Leak
I want to train a machine learning model that can determine the sentiment of tweets about different stocks.
To do this I have a dataset, lets call it A. For dataset A about 30% of the data is labelled....
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1
answer
8
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Unsupervised ranking of samples
Say I have a dataset of n samples. I want to maximize every feature’s value. I’m not sure if feature 1 is more important than feature 2, etc. Are there any methods of ranking my samples out there? If ...
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1
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16
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How to cluster based on sensor data? - My first data science job
I'm on my first (real), data, programming job. As everyone can imagine, this can be quite hard and I learn a lot from it, given I am a data science student in university. However, I am completely ...
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10
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How to get same output with reference model
I have a tflite model which was working with a random script on swift and I decided to add some more classes on an object detection aim. Training with the new classes didn’t work. The first model was ...
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1
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11
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Integrating time context in a machine learning model
Basically, what I'm curious about, are there any methods in machine learning to make the model take into account events that happen in real time that affect the data points during that time period. ...
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1
answer
11
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Filling na values with condition from other column
I am working on famous titanic dataset and I want to replace na values in Age column but on such a condition that these people whose Pclass=3 receive 25, Pclass=2 29 and Pclass=1 38.
I was trying to ...
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12
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Why facenet works better than siamese network
I have been reading about face recognition literature. I stumbled upon siamese networks with contrastive loss and the facenet paper. Both approaches use metric learning. The difference is mainly in ...
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41
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ChatGPT: How to use long texts in prompt?
I like the website chatpdf.com a lot. You can upload a PDF file and then discuss the textual content of the file with the file "itself". It uses ChatGPT.
I would like to program something ...
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19
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General question on the test and train data
Currently I'm working on a Kaggle problem. I have to predict an outcome by the given information. There are few metafiles for training a model with lots of features (>30). However, in the test file ...
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1
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1
answer
26
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Making a netcdf data using xarray
I am very very new to the world of data science as I only started using it in my new job so I would really appreciate help from the community experts (maybe also in simple words :)).
I am trying to ...
- 113
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1
answer
16
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Why the label is not explicitly involved in the loss function of skip-gram?
I am recently learning word embedding myself. When learning skip-gram from the paper https://arxiv.org/pdf/1310.4546.pdf[Distributed Representations of Words and Phrases and their Compositionality], I ...
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9
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How to get data directory in Microsoft Azure Machine Learning Studio
I am working on a CNN project, and I would like to read the data from an excel file. However, I am unable to find the proper path for it. I uploaded the data in the "Notebooks" file section. ...
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10
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What are the state-of-the-art knowledge distillation methods?
I need to implement some state-of-the-art knowledge distillation (KD) methods to distill dark knowledge of the teacher network to the student network with Pytorch.
I would really appreciated to any ...
- 1
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0
answers
15
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Very different behaviors between PSI and KS tests for data drift
I want to set up a process for data drift and I am trying to see which metric to pick. Using KS test, it flags half of my features to be drifted although when I look at the distribution between the ...
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8
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Difference between Validation Error on Learning Curve and Validation Error Calculation in Machine Learning Model
I am encountering a problem where the validation error I see on the learning curve of my machine learning model is different from the validation error I calculate using the mean squared error function....
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7
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For Q&A NLP system, how to extract the most relevant embedding if it is a combination of top K embeddings?
From my understanding, a typical "AI" Q&A system has a (vector) database of embedded text (from a set of documents). And when a user asks a question, the user's question is embedded and ...
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6
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Normalization followed by inverse normalization: loss of precision?
I have a neural network pipeline where I train GANs on a latent representation obtained from an autoencoder. To improve GAN stability, I would like to normalise the latent representation of the ...
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1
answer
20
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Maximizing minimum correlation
What meaning has the weighted sum of a group of variables so that each weight is assigned to maximize the minimum resulting correlation of all these variables to the sum obtained?
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10
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How to calculate threshold values for a simple binary classification model
Consider a binary classification problem with two features. Let's assume that the higher the value of each feature the more likely a datapoint is to be positively classified.
Additionally assume we ...
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1
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36
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Convert cosine similarity to probability
In natural language processing, the cosine similarity is often used to compute the similarity between two words. It is bounded between [-1, 1]. Supposedly, 1 means complete similarity, -1 means ...
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7
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How to add query filter to the Nearest Neighbors algorithm?
I have Nearest Neighbors model, built with sklearn sklearn.neighbors.NearestNeighbors, which I use to make content based recommendations.
Sometimes I need to ...
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1
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11
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What are the constants in this formula for polytrophic head?
Polytrophic head can be expressed as H = b1N^2 + b2NQ + b3Q^2 where b1, b2 and b3 are constants, N is the speed of the compressor (rmp), and Q is the volumetric flow rate of natural gas at the ...
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