Data Science Stack Exchange
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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.

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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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 prediction use case: House prices change over time thus…
thebluephantom
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Query data dimension

import numpy as np from sklearn import preprocessing, cross_validation, neighbors import pandas as pd from sklearn.linear_model import LinearRegression df = pd.read_csv('Downloads/breast-cancer-wisconsin.data.txt',skiprows=1) df.replace('?',…
Briancheung
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Is there a good deployment module using Golang's amazing single binary compilation model?

From my limited understanding, it's quite annoying trying to deploy models like PyTorch. So one would need something like ONNX. But another approach like Golang with a single binary is VERY attractive. I have used Golang before and it's reasonably…
xiaodai
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How to model the unknown in data science

I have been asked this question in interview which I was not sure how to respond. Situation: My company provides personal loans where consumer income is minimum $10,000 per annum and we have data to analyze the default/ delinquency history of these…
Abhi
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How to combine two different machine learning models, to get the combined result?

To further explain my question, I will explain my use-case. Say I have a model which is trained for how good/bad a food is for obesity based on its nutrition facts. And another model for, say hypertension. I wish to combine these models to be able…
Purvaudai Singh
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How does resnet model restores the skipped layers as it learns the feature space?

From the definition of resent from wikipedia: it is mentioned that resent model uses fewer layers in the initial training stages. This speeds learning by reducing the impact of vanishing gradients, as there are fewer layers to propagate through. The…
vinaygarg
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When does fitting happen in KNN?

In training session, model fitting happens to reduce error. But does KNN do this? Reducing error only happens due to changing K value and number of features, isn't it? So training set and test set is only for do things below, right? Train…
Jinwoo Lee
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What models do Create ML and Turi Create use

I'm taking a course on Apple's machine learning technologies. I just came across this paragraph: Turi Create and Create ML are task-specific, rather than model-specific. This means that you specify the type of problem you want to solve, rather…
Martin Muldoon
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Building a model in two stages

This question is regarding a use case related to predictive maintenance. The final model built (based on the steps mentioned below) is used to predict the failure of a particular component for a particular type of device. In the Machine Learning…
Arnab Biswas
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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 understand how important feature transformation is to…
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Supply chain model

Looking to build a supply chain model. This would include weather data, shipping data, supply and demand levels. Ultimate goal is to predict price using such a model. Any ideas on how to develop something like this, any sample code, any previous…
Ibrahim Mukherjee
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How to handle non-numeric user id's in a recommendation model

Hi i'm working on a practice project on amazon movie reviews and i did everything that was asked except building a model that will recommend movies to users which have not been watched nor been rated. but when i'm trying to train and split the model…
Yaya
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Estimating the accuracy of a model?

Given that I have a machine learning model. I evaluated the model over several labeled datasets and acquired the accuracy (or any other metrics) for these datasets. Now I receive a new dataset without labels. I run the model and got the…
mommomonthewind
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Corelation between overtime and sick leave

I have a scenario where I have to identify employees, who when take sick or any other paid leave his/her colleague (any other employee) gets overtime. My data set is as follows: employee_code----period---Leave_hours--- Overtime hours How to…
Zaka
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Working with Numerical/Continuous Dependent Variable and Numerical Independent Variable

I am working with a data set that has both numerical/continuous data as well as categorical data. I know I can use one-hot encoding as a method when preprocessing the data, but ultimately I'd like to know what should be the ML algorithm to consider…
Jessica Wade
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