Questions tagged [machine-learning]
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
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Prediction of Quarterly Financial Numbers
The task is to predict the quarterly revenue numbers using machine learning. Only 28 quarterly data points for financial numbers are available as companies release the revenue data quarterly. I have ...
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Feature selection for siamese network
I have a regression problem for which two observations are compared by a siamese-like Multilayer Perceptron.
Each observation 'O' is described by a feature vector 'X' of a certain number 'N' of ...
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How can I approach this transactions data problem?
I am trying to approach the following problem: Imagine that I am a bank and I have a dataframe of transactions that customers make, the columns that this dataframe has are transaction date, customer ...
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What is the reason behind high frequency output from LSTM model?
Following is the time history response of my input features, which has relatively low frequency component
My LSTM network architecture is as follows:
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Very basic but how to understand data statistically for machine learning?
I’m trying to solidify my statistics so I really know how to use them in my analysis/models. However my concept of statistical testing gets completely messed up by context. I’m unsure defining exactly ...
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Stable test in online time series forecasting problem
I have a Time Series Forecasting problem. You can think of it as predicting the daily closing prices of Apple stocks. My data is divided into 4-day segments, and the forecasting is based on predicting ...
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Why are low probabilities problematic for knowledge destilation?
Recently, I have been reading the Knowledge Distillation paper (Distilling the Knowledge in a Neural Network) and I have two main questions:
Neural networks typically produce class probabilities by ...
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Actual values vs Preditec values plot
I was working on a project and I got a 0.98 R^2 score on both the training and test data sets and 0.91 training mse and 1.02 test mse, But my Actual values vs Predicted values looks like this, I was ...
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Outliers problem
everyone hope you all are good.
I have a hard time with outliers
First i found some outliers in train set then i capped them and did the same with test set. So when i checked my rsme root mean ...
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How does the stacking works?
Suppose that I have $n$ trained weak base models: $m_1, m_2, ..., m_n$
As I understand after training that models we get their predictions on validation dataset, let's consider single element of ...
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Environment doesn't exist error gym_anytrading
I am trying to create the environment using gym_anything and I got an error that the environment doesn't exist.
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Semantic search with pretrained BERT models giving irrelevant results with high similarity
I'm trying to create a Semantic search system and have experimented with multiple pretrained models from the SentenceTransformers library: LaBSE, MS-MARCO etc. The system is working well in returning ...
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Cannot load audio files using AudioSegment
I am trying to load an mp3 file using pydub's AudioSegment method with below code.
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How do we modify the early stopping procedure to account for better losses after initial rise in losses?
I have a question regarding the usage of early stopping in the training of my forecasting model. Curious about how the training would go without early stopping, I observed that the test loss seems to ...
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Comparing a classfiers performance across distinct testing datasets
I have a dataset split into training, validation, and testing sets. I trained this model on the training data and evaluated on the validation and testing sets. Now I have an additional set of data ...
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Detecting material separation in images
I have an image set of material flowing through a spiral witch separates two types of mass based on their weight. I need to be able to detect where the mass separates vertically in the image. When ...
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Supervised or Unsupervised Learning Classification: Facebook Prophet vs. ARIMA
I'm currently exploring time series forecasting and considering the use of Facebook's Prophet and ARIMA models. I'm a bit confused about whether these approaches fall under supervised or unsupervised ...
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Is there anyway to evaluate the estimation results of least square
Consider the scenario where a practical problem is tackled utilizing the method of least squares. Upon each iteration, an estimation of the parameter $\theta$ is derived via $\hat{\theta} = (X^\top X)^...
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With infinite observations, would the weights resulting from ridge regression be the same as simple linear regression?
As the number of observations approaches infinity, do the weights of a linear regression approach the weights of a linear regression with L2 penalty?
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Align Vectors are Easy to Learn?
I have three vectors $x,y_1,y_2\in\mathbb{R}^{n\times 1}$, where $x=y_1$, $x\perp y_2$. If I use $x$ as input of a 2-layer perceptron, will regressing $y_1$ be easier than $y_2$ (i.e., when fully ...
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Can we use the word "federated learning" for non-machine learning solutions?
My question is can we use "learning" when we don't employ deep learning or a ML model but simply "learning" from the data using basic statistics?
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Generator loss not decreasing while training GAN
I’ve been attempting to create a basic GAN to generate images using this database of flowers (https://www.robots.ox.ac.uk/~vgg/data/flowers/102/).
I’ve spent a few days on this, and largely based my ...
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How to choose the right typt of ANN architecture for a regression model
So, im working on a project where i am leveraging ai to get accurate price predictions in terms of houses and real estate properties. I would like to use an artificial neural network so now i have to ...
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Data Science in Law Enforcement/National Security
I'm a senior undergrad in the US currently, and I will be graduating this spring with BS degrees in data science and mathematics. Up to this point, I have primarily studied statistics, data analysis, ...
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【NLP】Is there a model or task that determines contextual similarity?
I am trying to work on an engagement detection task in which I have to determine if a student is engaged in class.
I am looking for an NLP approach where I can calculate the similarity score of a ...
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For Finetuning Llama 2, what form of data is required?
I am working on a customer service chatbot project. I have files of different product's manuals on which i need to train the LLM which is Llama 2. As these are manuals so they not in Q/A form. In this ...
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How to use additional features in image captioning?
I have the following question - is it possible to train a model based on Transformer architecture to use additional attributes to generate a caption for an image?
For example, I have a dataset with ...
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Avoid killing learnable parameters when transforming input into intervals
I'm trying to make a model using Pytorch which is training and transforming a set of coordinates, and then is downsampled using the model below. However, when I'm making the input coordinates into ...
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Numerical issue with softmax regression implementation on MNIST
I'm having numpy numerical issues with my implementation of softmax regression/multiclass logistic regression on the MNIST dataset.
The numpy exp and log numerical issue goes away when I divide the x ...
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Which image classification methods/models could suit my (product) image classification problem?
Say you are a potato chips company. The goal is to have consumers upload images of the product they are having issues with and be able to identify the product by brand/variant using machine learning. ...
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Is there an online Vicuana model demo that supports plugging in embeddings directly?
I'm doing some work with using multi-modal data with LLMs like LLaMA and Vicuana. For example, something similar to Video-LLaMA, which converts images/videos into embeddings, concatenates it with the ...
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What does maximize average log probability mean?
In the word2vec paper (https://arxiv.org/pdf/1310.4546.pdf) that introduces the skip-gram algorithm we encounter this phrase:
which says that we maximize the average log probability.
Can someone help ...
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Interpreting large discrepancies between Specificities & the # of Extraneous Variable Models selected by a variable selection algorithm
I am going to preface my question by saying that this problem of interpretation I have run into is in the context of me doing my part as a collaborator on a statistical learning paper for the first ...
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Clustering or Finding Similarities Among Portfolio Allocations
I am trying to cluster a set of portfolios with percentage allocations among Stock, Bond, Other, and Cash. I am not sure what's the best way to go about this because the variables are interdependent ...
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Error while using saved logistic regression model on scoring vector data -The columns of A don't match the number of elements of x. A: 6011, x: 232964
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I'm getting error while using saved logistic regression model on scoring vector data.
SparkException: [FAILED_EXECUTE_UDF] Failed to execute user defined function (ProbabilisticClassificationModel$$...
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Why do we need hyperparameter tuning in Scikit learn? Doesn't sk learn models by default give best model?
When I have the option to build a classifier like this directly
clf = RandomForestClassifier()
why do we perform tuning by restricting the parameters like this
<...
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Clustering words with similar meanings
What methods are there to cluster words/word phrases with similar meanings together from a list of words/word phrases?
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overfitting or not
Hello so i'm building a classification model i train my on various models and these are the metrices so i want to know if ther's an overfitting or not
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How to build a categorization system without a target variable?
The data
I have a large dataset containing execution logs from various tests conducted over several years. The logs can be noisy and often contain a plethora of messages detailing the ongoing ...
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ML paper reproducibility
How can I reproduce results in an ML paper if I don't have the identical resources to train the models as in the paper ? (in my case I only have a laptop spec NVidia gpu and in most of the papers I ...
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Expanding Training Data for Intent and Entity Recognition Model
I have a specific use case where I need to identify both intent and entities within a given statement. For example, given the statement "Book train tickets from Mumbai to Delhi," the intent ...
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How Can I Train a Real-World-Ready Classifier with Limited Real Data and Abundant Open-Source Data?
I am trying to train a text classifier with open-source data to generalize on the real user traffic (henceforth "real data"). However, even though I have many annotated open-source data, I ...
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Optimizing decision tree
I have a question regarding the technique/technology which could be applied for the issue:
Suppose I have a rule-based tree or decision tree which predicts a variable Y based on variables A,B,C. This ...
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Utilizing Colab's GPU/TPU to Speed Up General Python Code not just data science code
I am new to using Colab and trying to speed up my code by utilizing the GPU/TPU runtimes. I have a block of plain Python code without any data science libraries like TensorFlow or PyTorch. I was able ...
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Understanding Multi-headed Attention from architecture details
I've a conceptual question
BERT-base has a dimension of 768 for query, key and value and 12 heads (Hidden dimension=768, number of heads=12). The same is conveyed if we see the BERT-base architecture
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Why is it difficult to use a linear regression model for the classification problems?
Why is it difficult to use a linear regression model for the classification problems?
user155516
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LSTM - How can I predict the status an hour before in advance?
I’m very beginner, I’m trying to design a prediction model for forecasting the status one hour ahead.I have 150 sample data, each consisting of of 24 hours of time-series data with multiple features (...
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Best practices on encoding on an increasing number of categorical variables
I'm currently using Gradient Boosting Regressor as my model to predict production risk based off a set number of features as a side-project. One of these features, ...
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What does "explicit latent variable optimization" mean?
The paper MotionLM: Multi-Agent Motion Forecasting as Language Modeling states:
Our model, MotionLM, provides several advantages: First, it does not require anchors or explicit latent variable ...
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