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In this article, we will go through the below points.What is an Exception in PowerShell?Terminating and Non-Terminating errors.Using Try / Catch block.Converting Non-Terminating error to Terminating Errors.Handling actual exception messages.What is the exception in PowerShell?Exception in PowerShell or other programming languages is the error or unexpected result that can be handled. For example, File not found while executing, dividing a number by zero.The exception can stop script execution if not handled properly.Terminating Errors and Non-Terminating ErrorsNon-Terminating errors don't halt script execution and it continuously runs script even if it is detected in the script. Below is an example of the ... Read More
In this article, we will work with CSV files in PowerShell which is considered one of the most efficient ways to deal with data.We have considered the below points for this article.Exporting data to the CSV file using PowerShell.Importing data from the CSV file using PowerShell.Let’s get started.Exporting data to the CSV file using PowerShellUsing Direct command outputTo export data to the csv file in PowerShell we can use Out-File which is the common cmdlet for storing the output to the file. The below command will get the top 10 CPU-consuming processes in the csv file.ExampleGet-Process | Sort-Object CPU -Descending ... Read More
OverviewPowerShell DSC is different than PowerShell scripting which ensures the remote windows systems are in the desired state and it is the declarative method unlike PowerShell Scripting and other programming languages which are considered imperative methods.In this article, we will go through the Push Method of the DSC which is a commonly used method for beginners and doesn’t require the Pull server. Pull server which polls the remote servers at some intervals and set the desired configuration for them and it is kind of automated.For the Push configuration, we will consider the below aspects.Get the DSC resource to Configure.Create the ... Read More
What is Azure State DSC?Azure State DSC is nothing but the DSC (Desired State Configuration) for the Azure VMs and can be configured from the Azure Automation Account. For the DSC there are two methods Push and Pull configuration but Azure is by default using the Pull server which constantly polls the target nodes and sends the configuration to the nodes.Azure DSC is itself a vast topic, in this article we will try the below configuration using PowerShell.Compose / Upload Node Configuration file.Compile node configuration.Attach compiled node configuration to the nodes.PrerequisiteAzure SubscriptionAzure Automation AccountConfiguration file (That we will create in ... Read More
In Fractional knapsack problem, a set of items are given, each with a weight and a value. We need to break items for maximizing the total value of knapsack and this can be done in greedy approach.AlgorithmBegin Take an array of structure Item Declare value, weight, knapsack weight and density Calculate density=value/weight for each item Sorting the items array on the order of decreasing density We add values from the top of the array to total value until the bag is full, i.e; total value
There are the major steps involved in data preprocessing, namely, data cleaning, data integration, data reduction, and data transformation as follows −Data Cleaning − Data cleaning routines operate to “clean” the information by filling in missing values, smoothing noisy information, identifying or eliminating outliers, and resolving deviation. If users understand the data are dirty, they are unlikely to trust the results of some data mining that has been used.Moreover, dirty data can make confusion for the mining phase, resulting in unstable output. Some mining routines have some phase for dealing with incomplete or noisy information, they are not always potent. ... Read More
An attribute is a data field, defining a characteristic of a data object. The nouns attribute, dimension, feature, and variable are used correspondently in the literature. The dimension is generally used in data warehousing. Machine learning literature influence to use the term feature, while statisticians prefer the method svariable.Data mining and database experts generally use the term attribute. Attributes defining a user object can include, for instance, customer ID, name, and address. Observed values for a given attribute are referred to as observations.A set of attributes can define a given object is known as attribute vector (or feature vector). The ... Read More
There are various aspects of mining methodology which are as follows −Mining various and new kinds of knowledge − Data mining covers a broad spectrum of data analysis and knowledge discovery services, from data characterization and discrimination to relations and correlation analysis, classification, regression, clustering, outlier methods, sequence methods, and trend and computational analysis.These services can use the same database in multiple ways and need the development of several data mining techniques. Because of the diversity of software, new mining services continue to emerge, developing data mining a powerful and fast-increasing field.For instance, for effective knowledge discovery in data networks, ... Read More
A web search engine is a specialized computer server that searches for data on the Web. The search results of a user query are restored as a list (known as hits). The hits can include web pages, images, and different types of files.There are various search engines also search and return data available in public databases or open directories. Search engines differ from web directories in that web directories are supported by human editors whereas search engines works algorithmically or by a combination of algorithmic and human input.Web search engines are large data mining applications. There are several data mining ... Read More
Classification is the procedure of discovering a model that defines and categorize data classes or concepts. The model are based on the search of a set of training data (i.e., data objects for which the class labels are famous). The model can predict the class label of objects for which the class label is anonymous.The derived model can be represented in several forms, including classification rules (i.e., IF-THEN rules), decision trees, numerical formulae, or neural networks. A decision tree is a flowchart-like tree architecture, where each node indicates a test on an attribute value, each branch defines an outcome of ... Read More