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NEW QUESTION # 96
Which of the below is the correct definition of "recall" in UiPath Communications Mining?
Answer: D
Explanation:
Recall is a metric that measures the proportion of all possible true positives that the model was able to identify for a given concept1. A true positive is a case where the model correctly predicts the presence of a concept in the data. Recall is calculated as the ratio of true positives to the sum of true positives and false negatives, where a false negative is a case where the model fails to predict the presence of a concept in the data. Recall can be interpreted as the sensitivity or completeness of the model for a given concept2. For example, if there are 100 verbatims that should have been labelled as 'Request for information', and the model detects 80 of them, then the recall for this concept is 80% (80 / (80 + 20)). A high recall means that the model is good at finding all the relevant cases for a concept, while a low recall means that the model misses many of them.
References: 1: Recall 2: Precision and Recall
NEW QUESTION # 97
What is the order of steps for automatically retraining and deploying a Document Understanding ML Model in Al Center with data from Document Validation Action?
Instructions: Drag the steps found on the "Left" and drop them on the "Right" in the correct order.
Answer:
Explanation:
Explanation:
To automatically retrain and deploy a Document Understanding Machine Learning (ML) Model in AI Center with data from the Document Validation Action, the steps should be followed in this order:
* Send Human in the Loop data to the used Dataset.
* This step involves sending the data that has been validated and corrected by human reviewers to the dataset. This data will be used for training the ML model.
* Use the Export feature from Document Manager using Scheduled Export.
* After the data is reviewed and validated, it needs to be exported from the Document Manager.
Scheduled Export automates this process, ensuring the dataset in AI Center is regularly updated with new data.
* Run Training/Full Pipeline in AI Center using Scheduled Pipeline with Auto-Retraining enabled.
* With the updated data in the dataset, the next step is to run the training or the full pipeline. The use of Scheduled Pipeline with Auto-Retraining ensures that the ML model is automatically retrained with the latest data.
* Enable the Auto Update feature in the ML Skill.
* Finally, enabling the Auto Update feature in the ML Skill ensures that the newly trained model is automatically deployed, making the improved model available for document understanding tasks.
Following these steps in the specified order allows for a streamlined process of continuously improving the ML model based on human-validated data, ensuring better accuracy and efficiency in document understanding tasks over time.
NEW QUESTION # 98
What are the UiPath Action Center action statuses?
Answer: D
Explanation:
The valid Action Center statuses are:
* Unassigned: The action is not assigned to any user.
* Pending: The action is assigned and awaiting user response.
NEW QUESTION # 99
What is the recommended split of documents for training and evaluation, considering a total of 15 documents per vendor?
Answer: B
Explanation:
When you create a training dataset for document classification or data extraction, you need to split your documents into two subsets: one for training the model and one for evaluating the model. The training subset is used to teach the model how to recognize the patterns and features of your document types and fields. The evaluation subset is used to measure the performance and accuracy of the model on unseen data. The evaluation subset should not be used for training, as this would bias the model and overfit it to the data1.
The recommended split of documents for training and evaluation depends on the size and diversity of your data. However, a general guideline is to use a 70/30 or 80/20 ratio, where 70% or 80% of the documents are used for training and 30% or 20% are used for evaluation. This ensures that the model has enough data to learn from and enough data to test on. For example, if you have 15 documents per vendor, you can use 10 documents for training and 5 documents for evaluation. This would give you a 67/33 split, which is close to the 70/30 ratio. You can also use the Data Manager tool to create and manage your training and evaluation datasets2.
References: 1: Document Understanding - Training High Performing Models 2: Data Manager - Creating a Dataset
NEW QUESTION # 100
What are all the ways to deploy Al Center?
Answer: C
Explanation:
UiPath AI Center can be deployed in multiple ways to meet different organizational needs and infrastructures. The available deployment options include:
* Cloud availability: Using UiPath's cloud services.
* On-premises air-gapped: A fully isolated, offline environment for organizations with strict security requirements.
* On-premises online: Deployed on-premise but with internet connectivity.
* Hybrid mode: Combining on-premises AI Center with on-premises Orchestrator for flexibility.
* Automation Suite: A comprehensive deployment of UiPath tools, including AI Center.
For more details, refer to:
* UiPath AI Center Deployment Models: Deployment Options
NEW QUESTION # 101
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