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NEW QUESTION: 1
You need to draw a straight red line between the start and end points of a calculated route.
Which code segment should you use?
A. var locationArray = new Array(); var len = route.Itinerary.Segments.length; locationArray.push(route.Itinerary.Segments[0].LatLong);
locationArray.push(route.Itinerary.Segments[len-1].LatLong); shape = new
VEShape(VEShapeType.Polyline, locationArray); shape.SetLineColor(new VEColor(255, 0,
0, 0)); layer.AddShape(shape);
B. var locationArray = new Array(); var len = route.Itinerary.Segments.length; locationArray.push(route.Itinerary.Segments[0].LatLong);
locationArray.push(route.Itinerary.Segments[len-1].LatLong); shape = new
VEShape(VEShapeType.Polyline, locationArray); shape.SetLineColor(new VEColor(255, 0,
0, 0.5)); shape.HideIcon(); layer.AddShape(shape);
C. var locationArray = new Array(); var len = route.Itinerary.Segments.length; locationArray.push(route.Itinerary.Segments[1].LatLong);
locationArray.push(route.Itinerary.Segments[len].LatLong); shape = new
VEShape(VEShapeType.Pushpin, locationArray); shape.SetLineColor(new VEColor(255,
0, 0, 0.5)); layer.AddShape(shape);
D. var locationArray = new Array(); var len = route.Itinerary.Segments.length; locationArray.push(route.Itinerary.Segments[0].LatLong);
locationArray.push(route.Itinerary.Segments[len].LatLong); shape = new
VEShape(VEShapeType.Polyline, locationArray); shape.SetLineColor(new VEColor(255, 0,
0, 0)); shape.HideIcon(); layer.AddShape(shape);
Answer: B
NEW QUESTION: 2
When Nuance/Speechworks OSR is installed, the variable SWIrunAsClient's value determines if
OSR client runs on a separate host than the server. That value is set __________.
A. Manually, as an Environment variable
B. Manually, in Speechworks.cfg
C. Automatically, in Speechworks.cfg
D. Conditionally, as an Environment variable
Answer: C
NEW QUESTION: 3
Which of the following are feature engineering techniques? (Select 2 answers)
A. Crossed feature columns
B. Hidden feature layers
C. Feature prioritization
D. Bucketization of a continuous feature
Answer: A,D
Explanation:
Explanation
Selecting and crafting the right set of feature columns is key to learning an effective model.
Bucketization is a process of dividing the entire range of a continuous feature into a set of consecutive bins/buckets, and then converting the original numerical feature into a bucket ID (as a categorical feature) depending on which bucket that value falls into.
Using each base feature column separately may not be enough to explain the data. To learn the differences between different feature combinations, we can add crossed feature columns to the model.
Reference:
https://www.tensorflow.org/tutorials/wide#selecting_and_engineering_features_for_the_model