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down into returns and replacement process. Take a replacement, there are the same goods replacement, the same value of different goods exchange, different value of different goods and other items, and then involved in promotions, points, discounts, concessions, inventory, compensation, whether door-to-door replacement and so on, the impact of many aspects of the return process is more complex. Excluding malicious, temporary changed mind, no matter, the general user will not arbitrarily return g

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Audience{ @Before("execution(** com.xlx.Performance.perform(...))") public void silencephone(){ System.out.println("silencephone"); } @Before("execution(** com.xlx.Performance.perform(...))") public void takeSeats(){ System.out.println("takeSeats"); } @AfterReturning("execution(** com.xlx.Performance.perform(...))") public void applause(){ System.out.println("applause"); } @AfterThrowing("execution(** com.xlx.Performance.perform(...))") publ

1. User-based collaborative filteringThe user (user-based)-based collaborative filtering algorithm first looks for other users who are similar to the new user based on the user's historical behavior information, and predicts the items that the current new user might like based on the evaluation information of the other items by these similar users. Given the user scoring data matrix R, the user-based collaborative filtering algorithm needs to define the similarity function s:uxu→r to calculate t

rating is the average value of the user's rating for all items.NM is the number of items (film); rateing (IJ) is the user I score for Project J.Thirdly, user I scored for item J is "User I score mean for all items" + "All users scored mean for Project J"-"overall score mean"The three methods are scored as follows:As you can see, the third method considers both the project and the user preference, which is better than the other two methods.2, "Simple method": User-based collaborative filteringTh

: 7. Pearson correlation coefficient (Pearson correlation coefficient)-pearsoncorrelationsimilaritythat is, correlation coefficient r in correlation analysis, the cosine angle of space vector is computed for x and y based on their overall normalization. The formula is as follows:? 8. Cosine similarity (cosine similarity)-cosinedistancemeasure?Is the cosine of the angle between the two vectors.Th

Category Name Keywords Supervised Classification Decision tree Information Gain Classification regression tree Gini index, Gini 2 Statistics, pruning Naive Bayes Non-parameter estimation, Bayesian Estimation Linear Discriminant Analysis Fishre identification, feature vector Solution K nearest Similarity measurement: Euclidean distance, block distance, editing distance, vector angle,

to determine, easy to get into local minima, there are learning phenomena, these defects in the SVM algorithm can be well solved.Source: Http://www.cnblogs.com/zhangchaoyangA summary of machine learning problem methods Big class Name Keywords Supervised classification Decision Tree Information gain Categorical regression Tree Gini index, χ2 statistic, pruning Naive Bayesian Non-parametric estimation, Bayesian

Covariance> 0, positive correlation between X and Y Covariance Covariance = 0, X and Y independent Pearson Correlation Coefficient R value range: [-1, 1] 0.8-1.0 strong correlation Strong correlation between 0.6 and 0.8 0.4-0.6 moderate correlation 0.2-0.4 weak correlation 0.0-0.2 extremely weak or unrelated Applicable to Series and DataFrame types Method Description . Cov () Returns the covariance matrix.

used to convert: the smaller the distance, the greater the similarity Pearson correlation coefficient (Pearson Correlation coefficient) Pearson correlation coefficients are generally used to calculate the tightness of the connections between the two fixed-distance variables, and its value is between [ -1,+1].sx, Sy is the standard deviation of the

. With unit testing, we can inject mock objects into the Bookdal for unit testing without relying on other data sources. First, create an empty test class with the following code: public class BookDALTest {public void setUp() throws Exception { } public void testGetAllBooks() throws Exception { } public void testGetBook() throws Exception { } public void testAddBook() throws Exception { } public void testUpdateBook() throws Exception { In the following code, we inject the Bookdal object in a m

Collaborative filtering enables recommendations by comparing users to other users and data.We do not use the important attributes given by the experts to describe the objects to calculate their similarity, but instead use the user's opinion to calculate the similarity, which is the method used in the collaborative filtering. It does not care about the description attribute of the item, but rather strictly calculates the similarity according to many users ' opinions. The similarity measure is a E

equal to 75Command:X136 144 143 157 137 159 135 158 147 165158 142 159 150 156 152 140 149 148 155Var.test (X,y) Analysis of the data of the steelmaking furnace with five casesCommand:XYVar.test (X,y) Total test of two-item distribution Example six have a number of vegetable seeds of the average germination rate of p=0.85, now randomly selected 500 tablets, seed dressing agent for seed soaking treatment, the result of 445 germination, ask whether the seed coating agent has no effect.Command:B

# Wechatpay Payment SDK for go! Includes all the features paid by the merchant! Easy integration! Directly on the link: [Payment SDK for Go] (https://github.com/liyoung1992/wechatpay) # # install ' Go get-u github.com/liyoung1992/wechatpay ' # # Help if you encounter problems in the integration process, please contact: liyoung_1992@163.com## currently implemented interface-Scan code payment (NATIVE)-H5 Pay (mweb)-Public number payment (JSAPI)-app payment (APP)-Small program payment (JSAPI)-

;6, choose the alternative train, the alternative agent, purchase insurance and so on can improve the success rate of the robbery ticketthree. Order details, check the order details, ticket status, and ticket number, etc.Four. Cancel the order, the order can be canceled, the cancellation of the order no longer rob the ticket, cancellation: 1, the order has not been robbed of the ticket, 2, the ticket has not expired;Five. Apply for a refund, the issue

orders and delivery as soon as possible. Thank you!2, the customer due to the size of the order of goods caused by the returnDear XXX,Thank much for your great support on us. So sorry for the inconvenience that XXX would it be possible to give others as a gift? Or How are we make a partial refund as a a-to-make-for-this?Just suggestion, if you insist on returning it back, we'll go to the further step.Waiting for your reply.Dear customer, Thank you ve

The common problems of shopping on Dangdang are as follows: Q: My order with fast payment time to pay more than once, can I have a refund? Payment will be paid after the order (not including the day) of the 5 working days automatically in accordance with the payment method refund, please note that check; Q: How long does it cost to restore the voucher amount when the purchase order is not signed, not del

Tags: refund Business Unwind code cell solution str Design pngRound and round, suddenly found that I am now an old driver, has been writing code are very busy, did not put a lot of bits and pieces of the record, today began a series, analysis of the year I contacted or I designed the table structure, there are good and bad, there is joy and tears. A lot of practical experience comes from stepping on one after another, from the perspective of the prese

the estimation error in the division process. The best story can be completed within an iteration cycle. If it is too large, you should consider splitting it into multiple user stories with smaller granularity. Testable: testable I personally think this is of the highest importance to user stories among all features. First, if a user story cannot be tested, it cannot be determined whether the story is complete. In addition, the corresponding acceptance test should also be automatically run, so

becomes 0-- Reverse the receipt Ar_cash_receipts_all the status to Revar_cash_receipt_history_all adds a record with a status of reversed and Current_record_flag to Y. The Current_record_flag of the original record is set to the empty ar_payment_schedules_all status to CL, and amount_due_remaining changes to 0 verification. --Payment Cancellation ar_cash_receipts_all No change ar_cash_receipt_history_all no change ar_payment_schedules_all nBsp;amount_due_remaining to the original remaining amo