Answer:
hope you find it right
Explanation:
The process of writing computer instructions in a programming language is known as Coding.
A computer program is usually written by a computer programmer in a programming language. From the program in its human-readable form of source code, a compiler can derive machine code—a form consisting of instructions that the computer can directly execute.
That line of code is written in the Python programming language. Put simply, a programming (or coding) language is a set of syntax rules that define how code should be written and formatted. Thousands of different programming languages make it possible for us to create computer software, apps and websites.
In programming, code (noun) is a term used for both the statements written in a particular programming language - the source code , and a term for the source code after it has been processed by a compiler and made ready to run in the computer - the object code .
Answer:
A. PII
Explanation:
PII (Personally identifiable information) is any data that will be useful in identifying a particular individual e.g full name, date of birth, etc. A donors detail in the database will surely be the data to be used to identify him personally.
Answer:
The various reasons that could be a major problem for the implementation are it involves a large number of parameters also, having a noisy data
Explanation:
Solution
The various reasons that could be causing the problem is given as follows :
1. A wide number of parameters :
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In the ensemble tree method, the number of parameters which are needed to be trained is very large in numbers.
- When the training is performed in this tree, then the model files the data too well.
- When the model has tested against the new data point form the validation set, then this causes a large error because the model is trained completely according to the training data.
2. Noisy Data:
- The data used to train the model is taken from the real world . The real world's data set is often noisy i.e. contains the missing filed or the wrong values.
- When the tree is trained on this noisy data, then it sets its parameters according to the training data.
- As regards to testing the model by applying the validate set, the model gives a large error of high in accuracy
y.