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Evaluating Performance of Models
After completing some data science projects in logistic regression and binary classification I have decided to write more about the evaluation of our models and steps to take to make sure they are…
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Different Model Evaluation methodologies — Part 2
Resubstitution method, also known as Residual method, is the most basic method and not recommended for model evaluation, due to its overfitting issue. The holdout evaluation method takes into account…...
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Evaluate your model properly
The progress we are seeing in machine learning is undeniable, in any given week, we see new algorithms being researched and theorised, new libraries being released to the open-source community and…
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Model Selection and Evaluation
This article is a continuation of a series I am writing on key theoretical concepts to Machine Learning. The other articles in this series are available on my page. Model Selection and Evaluation is…
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Model Selection & Assessment
A standard modeling workflow would see you partitioning your data into the training, validation, and testing sets. You would then fit your models to the training data, then use the validation set to…
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How to Evaluate your Machine Learning Model.
Evaluation metrics explain the performance of a model. An important aspect of evaluation metrics is their capability to discriminate among model results.
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Classification Model Evaluation
For classification problems, the first thing we need to know is the confusion matrix. From this matrix, we can acquire some useful information, including accuracy, precision, recall, and f1 score…
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Introduction to Machine Learning Model Evaluation
ML models have a significant impact on our lives, they are involved in sensitive issues such fraud detection, autonomous driving and deciding which content will be displayed to millions of users 24…
Read more at Becoming Human: Artificial Intelligence Magazine
Classification Model Assessment
The human brain is a complex organ and is capable of recognizing patterns, regularities and irregularities through many experiences over a lifetime. We remain calm and assured when we know that an…
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Performance measures of models
Schools and colleges regularly conduct tests. The basic idea behind this is to measure the performance of the students. To understand which is their strong subject and where they need to work harder…
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Model Evaluation I: Precision And Recall
To test the quality of any classification system like Support Vector Machines, there’s need to perform some evaluation metrics. Support Vector Machines are classification algorithm which I explained…
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Measuring Model Goodness — Part 1
Data and AI are transforming businesses worldwide from finance, manufacturing and retail to healthcare, telecommunications and education. At the core of this transformation is the ability to convert…
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Evaluating a Machine Learning Model
After creating a machine learning model, interpreting the model results and evaluation is important aspect of the machine learning workflow. In this post we will discuss different evaluation matrices…...
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Have you ever evaluated your model in this way?
Model evaluation by considering frequencies of false positives and false negatives. Finding probability of difference between cells of confusion matrices. Applying the McNemar's test for confusion mat...
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How to Measure the performance of a Model ?
Whenever we develop a model we do us a performance metric to go ahead with that model or not. If any of you don’t know what model to use when and why . Please go through this till end. After you…
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Model Diagnostics and Selection — 9
Building a model can be a never-ending process in which we constantly improve the model by adding interactions, taking away variables, doing transformations and so on. However, at some point, we need…...
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Evaluating Machine Learning Models
When the hard work of building a model is done, someone has to make the final decision of whether to press “go” and release the model into the wild. This is the crucial moment for a data scientist…
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Evaluating Regression Models
After building a machine learning model whether that is using simple linear regression or gradient boosting it is important to get an idea of just how well your model performs. This article is…
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Evaluating our Machine Learning model Performance
Model Evaluation is one of the most important steps in developing a machine learning pipeline. Just imagine, designing a model and then straight away deploying it on production. And Suppose, your…
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How to evaluate Machine Learning models? — Part 1
Before getting deep into artificial intelligence, it is important to understand which model should deploy? what are the metrics with respect to dataset and the application of model. Like a Teacher…
Read more at Becoming Human: Artificial Intelligence Magazine
Machine Learning — How to Evaluate your Model?
Basic evaluation metrics and methods for Machine Learning algorithms
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How to Check the Performance of Your Models
Evaluation metrics are the basis on which you judge the performance of your machine learning or deep learning models. It is an important step after model creation and before model deployment. Most…
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Evaluating Classification Models
A doctor wants to know if his patient has a disease. A credit card company is interested in determining if a certain transaction is a fraud. A graduate school candidate is interested if whether or…
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Model Validation
You've built a model. But how good is it? In this lesson, you will learn to use model validation to measure the quality of your model. Measuring model quality is the key to iteratively improving your ...
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