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NEW QUESTION: 1
Refer to the exhibit.
If R41 configured as table?
A. 0.0.0.0/0, 4.4.4.4/32 and 10.2.4.0/24
B. 4.4.4.4/32,10.2.4.0/24 and 2.2.2.2/32
C. 4.4.4.4/32 and 10.2.4.0/24 only
D. 0.0.0.0/0 and 4.4.4.4/32 only .
E. 4.4.4.4/32 and 10.1.4.0/24 only
Answer: C
NEW QUESTION: 2
You are developing an application that uses a third-party JavaScript library named doWork().
The library occasionally throws an "object is null or undefined" error with an error code of
-2146823281.
The application must:
Extract and handle the exceptions thrown by doWork()
Continue normal program execution if other exceptions occur
You need to implement the requirements.
Which code segment should you use?
A. Option B
B. Option A
C. Option C
D. Option D
Answer: C
Explanation:
Explanation/Reference:
* The try statement lets you test a block of code for errors.
The catch statement lets you handle the error.
The JavaScript statements try and catch come in pairs:
try {
Block of code to try
}
catch(err) {
Block of code to handle errors
}
* object.number [= errorNumber]
Returns or sets the numeric value associated with a specific error. The Error object's default property is number.
* Example:
The following example causes an exception to be thrown and displays the error code that is derived from the error number.
try
{
// Cause an error.
var x = y;
}
catch(e)
{
document.write ("Error Code: ");
document.write (e.number & 0xFFFF)
document.write ("<br />");
document.write ("Facility Code: ")
document.write(e.number>>16 & 0x1FFF)
document.write ("<br />");
document.write ("Error Message: ")
document.write (e.message)
}
The output of this code is as follows.
Error Code: 5009
Facility Code: 10
Error Message: 'y' is undefined
Reference: JavaScript Errors - Throw and Try to Catch; number Property (Error) (JavaScript)
NEW QUESTION: 3
アプリケーションシステムの合意されたサービスレベルが満たされていることを示す最良の指標は次のうちどれですか。
A. 帯域幅使用ログ
B. CPU使用率レポート
C. セキュリティインシデントレポート
D. トランザクション応答時間
Answer: C
NEW QUESTION: 4
バイナリ分類を実行するリカレントニューラルネットワークを構築しています。
各トレーニングエポックのトレーニング損失、検証損失、トレーニング精度、および検証精度が提供されています。分類モデルがオーバーフィットしているかどうかを識別する必要があります。
次のうち正しいものはどれですか？
A. モデルのトレーニング時に検証損失が増加する一方で、トレーニング損失は減少します。
B. トレーニング損失は一定のままであり、検証損失はモデルをトレーニングするときに一定の値でトレーニング損失値に近いままです。
C. モデルをトレーニングするとき、トレーニング損失は一定のままで、検証損失は減少します。
D. モデルをトレーニングすると、検証損失は減少しますが、トレーニング損失は増加します。
Answer: A
Explanation:
Explanation
An overfit model is one where performance on the train set is good and continues to improve, whereas performance on the validation set improves to a point and then begins to degrade.
References:
https://machinelearningmastery.com/diagnose-overfitting-underfitting-lstm-models/