Answer:
Training data is used to fine-tune the algorithm’s parameters and evaluate how good the model is
Explanation:
The statement about datasets used in Machine Learning that is NOT true is "Training data is used to fine-tune algorithm’s parameters and evaluate how good the model is."
This is based on the fact that a Training dataset is a process in which a dataset model is trained for corresponding it essentially to fit the parameters.
Also, Testing the dataset is a process of examining the performance of the dataset. This refers to hidden data for which predictions are determined.
And Validation of dataset is a process in which results are verified to perfect the algorithm's details or parameters
Answer:
scope
Explanation:
Destructor is a member function and it call automatically when the class object goes out of scope.
Out of scope means, the program exit, function end etc.
Destructor name must be same as class name and it has no return type.
syntax:
~class_name() { };
For example:
class xyz{
xyz(){
print(constructor);
}
~xyz(){
print(destructor);
}
}
int main(){
xyz num;
}//end program
when the object is create the constructor will called and when the program end destructor will call automatically.
It’s two ways to analyze data
Here is an HTML example with the CSS class defined inline:
<!doctype html>
<html>
<head>
<style>
.YellowBackground {
background-color : yellow;
}
</style>
</head>
<body class="YellowBackground">
<h1>A yellow background</h1>
</body>
</html>
The least common multiple (LCM) of 78, 90, and 140 is: 16,380
78 × 210 = 16,380
90 × 182 = 16,380
140 × 117 = 16,380
