From testing, we acquired the following confusion matrix for brain cancedetection.no cancer 80cancer 120 28no cancer cancerUsing the confusion matrix from the notes, how many True Positives did ourmodel get correct?O80O 1228 Select all that apply. Which are the following properties of the Rosenblatt'sPerceptron cause it to be difficult to use in the real world?□ It is never guaranteed to convergeIt only converges for data that is linearly separableItonly works for binary classifcation tasksIt only works for data that contains more than 2 classes

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From testing, we acquired the following confusion matrix for brain cancer detection. no cancer 80 cancer 12 no cancer cancer Using the confusion matrix from the notes, how many True Positives did our model get correct? 2 8 O 80 O 12 2 8

From testing, we acquired the following confusion matrix for brain cancer detection. no cancer 80 cancer 12 no cancer cancer Using the confusion matrix from the notes, how many True Positives did our model get correct? 2 8 O 80 O 12 2 8

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Theoretical Computer Science

Usually, computer science seems like a practical field that involves studying, building, and working closely with computers. However, a subclass of this discipline also centers on the mathematical factors of the same. This is called theoretical computer science, and its focal point differentiates it from other branches of computer science: the rigorous mathematical approach it takes. This discipline falls under the umbrella of discrete mathematics, which is the study of countable or discontinuous mathematical structures.

Question

From testing, we acquired the following confusion matrix for brain cance
detection.
no cancer 80
cancer 12
0 2
8
no cancer cancer
Using the confusion matrix from the notes, how many True Positives did our
model get correct?
O
80
O 12
2
8

Select all that apply. Which are the following properties of the Rosenblatt's
Perceptron cause it to be difficult to use in the real world?
□ It is never guaranteed to converge
It only converges for data that is linearly separable
It
only works for binary classifcation tasks
It only works for data that contains more than 2 classes

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