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I have come across few (Machine learning-classification problem) journal papers mentioned about evaluate accuracy with Top-N approach. Data was show that Top 1 accuracy = 42.5%, and Top-5 accuracy = 72.5% in the same training, testing condition. I wonder how to calculate this percentage of top-1 and top-5?
Can some one show me example and steps to calculate this?
Thanks
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Evaluation is a process that critically examines a program. It involves collecting and analyzing information about a program's activities, characteristics, and outcomes. Its purpose is to make judgments about a program, to improve its effectiveness, and/or to inform programming decisions (Patton, 1987).
Evaluate definition An example of evaluate is when a teacher reviews a paper in order to give it a grade. (math.) To find the numerical value of; express in numbers. To determine the importance, effectiveness, or worth of; assess.
The main types of evaluation are process, impact, outcome and summative evaluation. Before you are able to measure the effectiveness of your project, you need to determine if the project is being run as intended and if it is reaching the intended audience.
Top-1 accuracy is the conventional accuracy: the model answer (the one with highest probability) must be exactly the expected answer.
Top-5 accuracy means that any of your model 5 highest probability answers must match the expected answer.
For instance, let's say you're applying machine learning to object recognition using a neural network. A picture of a cat is shown, and these are the outputs of your neural network:
Using top-1 accuracy, you count this output as wrong, because it predicted a tiger.
Using top-5 accuracy, you count this output as correct, because cat is among the top-5 guesses.
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