Hi Guest
MobileUser
HomePage
Jobs
WalkIn
Articles
Agile
DotNet
WebServices
Mathematics
OOPS
WEB
SharePoint
Java
DataBase
Artificial Intelligence
BigData
Android
XML
Agile
Software
SEO
Science Techonlogy
Repository Questions
PHP
Frameworks
Server
Testing
HR
Java
TPF
Tutorial
Tools
Test and Papers
Silverlight
Science Techonlogy
----- Select Country -----
----- Select Location -----
----- Select Category -----
:) Latest Topic
AJAX
VB.NET
SQL Query
UDDI
CLASS
JavaScript Questions
SharePoint Interview
SilverLight
WCF
general knowledge
ASP.NET
:) Hot Jobs
:) Latest Articles
Follow
When an ML Model has a high bias, getting more training data will help in improving the model.
Question Posted on 12 Jul 2020
Home
>>
Important Topics
>>
ML Exploring the Model
>>
When an ML Model has a high bias, getting more training data will help in improving the model.
When an ML Model has a high bias, getting more training data will help in improving the model.
Choose the correct answer from below list
(1)True
(2)False
Answer:-(2)False
0
0
Input Your Comments Or suggestions(If Any)
Name
Email
(optional)
Comments
Other Important Questions
____________ is the line that separates y = 0 and y = 1 in a logistic function.
What is the name of the function that takes the input and maps it to the output variable called?
____________ measures how far the predictions are from the actual values.
What is the range of the output values for a sigmoid function?
For ____________, the error is calculated by finding the sum of squared distance between actual and predicted values.
Top Searches:
asp net questions
vb net questions
sql query
uddl questions
class
javascript Questions
sharepoint interview questions and concept
silverlight questions and concept
wcf questions
beans
general knowledge
ajax questions
PHP
|
Biztalk
|
Testing
|
SAP
|
HR
|
Privacy policy |
Terms and Conditions
| Blog
If the copyright of any questions or content or syntax belong to you email us we will remove that(info@crackyourinterview.com or crackyourinterview2018@gmail.com)
Home
About Us
GroupChat
Sitemap
Feedback
Contact us