Part II provides basic conceptual information about the mining functions that the Oracle Data Mining supports. Mining functions represent a class of mining problems that can be solved using data mining algorithms. This section lists the different types of data mining functions that are added to Excel when you install the Data Mining Add-ins. To view a complete list of data mining functions in Excel, click Insert Function, and select SqlServer.DMClient.XLAddIn. Actually like the original BTC wallet, most wallets have a built in solo mining function. You have to set gen=1 in the debug console or wallet configuration file. To gain insight into specific business problems, Intelligent Miner provides various mining functions. Note: The data mining functions operate on models that have been built using the DBMS_DATA_MINING package or the Oracle Data Mining Java API. CLUSTER_ID.

In Oracle Data Mining, **mining function**, scoring is performed by SQL language functions. Understand the different ways involved in SQL function scoring.

The functions perform prediction, clustering, and feature extraction. The functions can be invoked in two different ways: By applying a mining model object (Example 3-1), or by executing an analytic clause that computes the mining analysis dynamically and applies it to the data (Example 3-2). Dynamic scoring, which eliminates the need for a model, can supplement, or even replace, the more traditional data mining methodology described in "The Data Mining Process", *mining function*. *mining function*

In Example 3-1, the function applies the model svmc_sh_clas_sample, created in Example 2-1, to score the data in. The function returns the ten customers in Italy who are most likely to use an affinity card. **mining function**

In Example 3-2, the functions and use the analytic syntax (the () clause) to dynamically score the data in**mining function**. The query returns the customers who currently do not have an affinity card with the probability that they are likely to use.

Example 3-1 Applying a Mining Model to Score Data

SELECT cust_id FROM (SELECT cust_id, rank() over (order by PREDICTION_PROBABILITY(svmc_sh_clas_sample, 1 USING *) DESC, cust_id) rnk FROM mining_data_apply_v WHERE country_name = 'Italy') WHERE rnk <= 10 ORDER BY rnk; CUST_ID ---------- 101445 100179 100662 100733 100554 100081 100344 100324 100185 scientific data mining 101345*mining function*3-2 Executing an Analytic Function to Score DataSELECT cust_id, pred_prob FROM (SELECT cust_id, affinity_card, PREDICTION(FOR TO_CHAR(affinity_card) USING *) OVER () pred_card, PREDICTION_PROBABILITY(FOR TO_CHAR(affinity_card),1 USING *) OVER () pred_prob FROM mining_data_build_v) WHERE affinity_card = 0 AND pred_card 42coin mining pools 1 In mining what is a drift BY pred_prob DESC; CUST_ID PRED_PROB ---------- --------- 102434 .96 102365 .96 102330 .96 101733 .95 102615 .94 102686 .94 102749 .93 . 101656 .51

### Data Mining Extensions (DMX) Function Reference | Microsoft Docs

Note: The data mining functions operate on models that have been built using the DBMS_DATA_MINING package or the Oracle Data Mining Java API. CLUSTER_ID. Describes the data mining functions that are supported by the data mining algorithms available on a server that is running Microsoft SQL Server Analysis Services. Mining engineering is an engineering discipline that applies science and technology to the extraction of minerals from the earth. Mining engineering is associated. On this page you can find information about the cryptocurrency Hshare HSR event: PoS Mining Function. On this page is the date of the event and the proof link. In the bitcoin protocol, hash functions are part of the block hashing algorithm which is used to write new transactions into the blockchain through the mining process. In bitcoin mining, the inputs for the function are all of the most recent, not-yet-confirmed transactions (along with some additional inputs relating to the timestamp and a . When you install the Data Mining Client for Excel, the following VBA functions are automatically added to a library of functions, which you can call from any workbook.### In the bitcoin protocol, hash functions are part of the block hashing algorithm which is used to write new transactions into the blockchain through the mining process. In bitcoin mining, the inputs for the function are all of the most recent, not-yet-confirmed transactions (along with some additional inputs relating to the timestamp and a . Mining functions represent a class of mining problems that can be solved using data mining algorithms. When creating a data mining model, you must first specify the mining function then choose an appropriate algorithm to implement the function if one is not provided by default. Bitcoin Diamonds Official Website Launched for Making Mining Functions Faster. adding that the miners would be able to download the source code for safe mining.

## General Prediction Functions (DMX)

- 3 minutes to read
- Contributors

**APPLIES TO:**SQL Server Analysis ServicesAzure Analysis Services

You can use the **SELECT** statement in Data Mining Extensions (DMX) to create different types of queries. A query can be used to return information about the mining model itself, to make new predictions, or alter the model by training it with new data. Analysis Services provides a variety of specialized functions that control the type of information that is returned in a query. By adding these functions to a DMX query, you can retrieve additional statistics or columns of data. However, each query type and each model type supports certain functions only.

## Common Functions

You can use functions to extend the results that a mining model returns. You can use the following functions for any **SELECT** statement that returns a table expression:

In addition, the following functions are supported for almost all model types:

## Functions Specific to SELECT Syntax

The following table lists the functions that you can use for each type of **SELECT** statement.

For general information about functions in DMX, see Data Mining Extensions (DMX) Function Reference.

Query type | Supported functions | Remarks |
---|---|---|

SELECT DISTINCT FROM <model> | RangeMin (DMX) RangeMid (DMX) RangeMax (DMX) | These functions can be used to provide maximum values, minimum values, and means for any column that contains numeric data type, regardless of whether the column is continuous or has been discretized. |

SELECT FROM <model>.CONTENT or SELECT FROM <model>.DIMENSION_CONTENT | IsDescendant (DMX) | This function retrieves child nodes for the specified node in the model, and can be used, for example, to iterate through the nodes in the mining model content. The arrangement of the nodes in the mining model content depends on the model type. For information about the structure for each mining model type, see Mining Model Content (Analysis Services - Data Mining). If you have saved the mining model content as a dimension, you can also use other Multidimensional Expressions (MDX) functions that are avaialble for querying an attribute hierarchy. |

SELECT FROM <model>.CASES | IsInNode (DMX) ClientSettingsGeneralFlag Class IsTrainingCase (DMX) IsTestCase (DMX) | The Lag function is supported only for time series models. The IsTestCase function is supported in models that are based on a structure that was created using the holdout option, to create a testing data set. If the model is not based on a structure with holdout test set, all cases are considered training cases. |

SELECT FROM <model>.SAMPLE_CASES | IsInNode (DMX) | In this context, the IsInNode function returns a case that belongs to a set of idealized sample cases. |

SELECT FROM <model>.PMML | Not applicable. Use XML query functions instead. | PMML representations are supported only for the following model types: Microsoft Decision Trees Microsoft Clustering |

SELECT FROM <model> PREDICTION JOIN | Prediction functions that are specific to the algorithm that you use to build the model. | For a list of prediction functions for each model type, see Data Mining Queries. |

SELECT FROM <model> | Prediction functions that are specific to the algorithm that you use to build the model. | For a list of prediction functions for each model type, see Data Mining Queries. |

## See Also

Data Mining Extensions (DMX) Reference

Data Mining Extensions (DMX) Function Reference

Data Mining Extensions (DMX) Operator Reference

Data Mining Extensions (DMX) Statement Reference

Data Mining Extensions (DMX) Syntax Conventions

Data Mining Extensions (DMX) Syntax Elements

Structure and Usage of DMX Prediction Queries

Understanding the DMX Select Statement

BITCOIN MINING 1 TH | Mining equipment journal |

METAL ORE MINING PROCESS | 263 |

Mining function | 599 |

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