Questions tagged [machine-learning-model]
A machine learning model is a simplified representation of a dataset, derived from statistics in the data, used to make predictions. It can represent patterns, behaviours or features within this dataset which have been learnt by the algorithm during training.
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How to add noise to supervised (binary-classifier)?
Note: The question is not about validating/testing a trained model.
Say i have an unlabeled features set, I want to approximate the true labels (for the sake of argument lets assume it's a binary ...
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Linear regression, R²?
When I do a linear regression, R²: 0.90, but the estimates are not correct, why is this happening?
(Deep Not : Adjusted R-squared: -0.3872)
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Python OneHotEncoder Using Many Dummy Variables or better practice?
I am building a neural network and am at the point of using OneHotEncoder on many independent(categorical) variables. I would like to know if I am approaching this properly with dummy variables or if ...
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Chi-square as evaluation metrics for nonlinear machine learning regression models
I am using machine learning models to predict an ordinal variable (values: 1,2,3,4, and 5) using 7 different features. I posed this as a regression problem, so the final outputs of a model are ...
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I got 100% accuracy on my test set,is there something wrong?
I got 100% accuracy on my test set when trained using decision tree algorithm.but only got 85% accuracy on random forest
Is there something wrong with my model or is decision tree best suited for the ...
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can accuracy rise while precision and recall drop?
I am working on a model and running some experiments, I see that under some configurations, The accuracy rises while the recall and precision are much lower, what is the mathematical explanation? is ...
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How to show value of a classification model even though it doesn't get the desired performance?
I developed a classification model for a telecom client. Where we classify between Dual-sim and non-Dual-Sim clients. After many iteration the best precision we can get is 60%. The contract says that ...
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Need help on Time Series ARIMA Model
I'm working on forecasting daily volumes and have used time series model
to check for data stationarity. However, I'm strugging at forecasting data with 90% accuracy. Right now variation is extremely ...
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How to train and validate a model continously which affects its own future data?
We are working with a online marketplace. Our problem is to predict whether certain products are profitable or not for our marketplace in near future(next one month horizon).
For example: Consider 2 ...
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Churn definition for non-contractual services
I am computing churn definition i.e, the number of days after which we will say a customer has churned in fashion retail, etc. Currently, I am using the transaction dates to get the average days ...
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Monitor Model Training Progress over HPC Clusters
As a part of my research in Deep Learning, I have to frequently train models which require a lot of computing power. As such, I use my university's HPC environment to submit my jobs and to train my ...
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How would I apply anomaly detection to time series data in LSTM?
I am using a LSTM RNN in Python and have successfully completed the prediction phase. My ultimate goal is anomaly detection. I'm hoping to have something like what you could see on Facebook Prophet, ...
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How to model a Machine learning problem considering links between features
Context:
To predict employee turnover ( will an employee leave? ), I have used one of the classification algorithms (LDA) to train my dataset, and then make predictions.
The dataset is quite small (...
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Predicting number of cars
I am predicting the number of cars from a traffic dataset.
Here is my data dictionary:
The ‘Traffic-Major-Roads(kilometres)’ file contains the following variables (variable names
are in bold):
Year - ...
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Why replacing null values with outliers?
I have been watching a tutorial on stock price prediction with multivariate linear regression and the tutor replaces missing value data, NaN, with the outlier -99999.
Why and how do replacements like ...
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Algorithms, techniques, papers for regression with vector output
I have a regression problem that has relatively low dimensional input (say 8 initial relevant features, without the engineered ones), but very high dimensional output vector (not a single value for ...
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Are there any methods of supervised learning that return a bitmap instead of a set of parameters?
For example, the SVM or ANN methods perform search of a surface which would separate the data points in a best way. This surface is returned in the vector or parametric form. Are there methods ...
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When is feature transformation required?
I was fitting machine learning models to clean data(Imputed missing values, removed unnecessary features etc). I didn't transform the features that are skewed. Before moving forward, I want to ...
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How to apply machine learning model to new dataset
I'm very new to machine learning & python in general and I'm trying to apply a Decision Tree Classifier to my dataset that I'm working on.
I would like to use this model to predict the outcome ...
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How much neural network theory required to design one? [closed]
So I have looked at some of the literature on neural networks and read some chapters, but the learning curve is so steep that I have had trouble even getting started on designing the neural network to ...
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Create Custom Python Model in Azure ML Studio?
I came across this article on how to create a Custom R Model and use it in Azure ML studio
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/create-r-model
Can we ...
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Classification using Orange 3
In Orange3 while only using its widgets, without writing Python code, I’ve implemented the following typical machine learning processes
Train a training set, (1 file)
Validating a validation set (e.g....
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Image resizing to be done programatically or taken care by model config file in tensorflow?
For Deep Learning using Tensorflow, is it necessary to resize the images to a predefined width and height before before training using a model?
OR
In model configuration file , I noticed this ...
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What is the best references / books to get familiar with machine learning algorithms? [duplicate]
I'm just starting off as a data scientist and i need to understand how regression, random forest and much more.. algorithms function under the hood, the maths behind them and when to use them. I ...
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Which machine learning algorithm to choose?
I want to choose an unsupervised algorithm which learns to predict $n$ outputs from the data, for eg. 4 coordinates (pixels) in an image. What algorithm should I choose? I think it's a 2-class ...
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Iterative Machine Learning
I was wondering what percentage of Machine Learning Algorithms are iterative in nature; i.e. I can run them sequentially, on different set of data and the model refines itself. Are there any ...
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Choosing the right model to learn [closed]
I'm new to the data science world, and I hope to solve a problem using deep learning methods, I started learning how FNN and CNN work and when I saw how many models and methods are the I got a bit ...
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How to properly represent a tic tac toe board to a CNN?
I'm figuring out how to manipulate convolutional neural networks (CNN) in python and I want to apply this kind of NN to an agent player that plays tic tac toe. I know that's weird and the problem ...
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modeling binary classification data
I am new to Machine learning. While reading SparkMLLib java code, I found Binary_classification dataset. But I am not able to understand how this data is modeled and if I want to model same type of ...
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What could be some Classification techniques to classify a tree of webpages given the category of each webpage
I want to perform a website classification task where I have modeled a website as a tree of webpages. I already have a model which can assign categories to the nodes in the tree (webpages). I need ...
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Build a predictive model for number of hockey goals in a season for an individual player
I'm looking to build a predictive model for hockey players individual statistics. My goal is to predict how many points a player can be expected to have at the end of the season.
To do so, I thought ...
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Model selection for a "set of linear models"?
I would appreciate your input on which predictive ML model(s) could fit our dataset the best.
The primary features of the dataset are x,y (continous) and c (factor with around L=500 unordered levels)....
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When to use Multinomial Naive Bayes?
I am working on a text classification problem, and plan on using Naive Bayes based model.
In which cases should I consider using Multinomial Naive Bayes?
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Different Values in Training and Testing set
If I am trying to build a classification model where Values for columns have different ranges: For Example: Column A in training set ranges from 0 - 30 but for testing set it ranges from 0 - 80.
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Is it possible to make an machine learning algorithm, that can outperform humans in complex games with current technology?
Would a company like OpenAi, it the "average" person be able to make a bot, using machine learning, that can outperform the best e-sport players in complex games, like PubG, with the technology we ...
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Split large dataset for predictive modeling using rsparkling -sparklyr
I am trying to build machine learning models (GBM, RF, Staking)
on top of a dataset that is about 3G in size on my local computer.
However, I only have 4G memory (only 2G are available).
My question ...
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What are the individual models within a machine learning ensemble called?
I am aware that an ensemble machine learning model is a stack of two or more machine learning models. Is there a word to refer to those individual models that go into the ensemble model? (i.e. a ...
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Temporal Aspects in Machine Learning
Concept drift means that the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways.
With reference to the classic house price ...
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Confused about the different aspects in Machine Learning [closed]
After reading different articles about ML and algorithms, scientist tends to use different words when describing the different aspects in ML.
So now I'm a bit confused myself and I hope you can ...
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Performance Evaluation Metrics used in Training, Validation and Testing [closed]
Which specific performance evaluation metrics are used in training, validation and testing and why? I am thinking error metrics (RMSE, MAE, MSE) are used in validation, and testing should use a wide ...
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Alternatives to Logistic Regression
I have age, gender, height, weight and some other similar parameters of 15000 subjects. I also have one column showing if they had a medical condition (present in about 20% subjects). I now want to ...
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How to continue incremental learning when a categorical variable has been assigned additional category labels?
Please help answer this question or point me to any resource.
There is a model in an environment where training happens with new data and the data is discarded after training is completed.
This keeps ...
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Feature has a pattern in relation to class but does not enhance classifier to predict class
I have a feature x that when I plot it again my class variable y it shows some sort of pattern, i.e. it is obvious that x has a relation with y, but when I add the x to my logistic model it reduce the ...
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Deciding Initial Weights In A Linear Classifier For Sentiment Analysis
I would like to build a simple sentiment analysis classifier using logistic regression. I downloaded a list of positive and negative words from cs.uic.edu. There are more than 6000 words both positive ...
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Encoding continuous values
I've been reading about one-hot encoding for categorical values. Could similar mechanism make sense for continuous values? I'm looking at a problem, where I try to predict the volume of product X, ...
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How to bypass ID column without being used in the training model but have it as output - Azure ML
The input data in the model includes column ControlNo.
But I don't want this column being part of learning process so I'm using Select Columns in Dataset to ...
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Using Machine Learning techniques for text-analysis
I am analysing a bunch of tweets and I want to understand which political party the authors support.
I am using Mathematica but I am thinking to re-write my code in Python. If you have any suggestion,...
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Predicting best time to send email
I have a dataset of past emails sent, when they were sent and if they were opened. What would be the best model to predict the best time to send email?
I was thinking of modeling it as time series ...
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Design language or artifact for data science model
Inspired from this question, given that there is no standard definition of a data-science model, is there a way to standardize the communication about any data-science model?
Just like material ...
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