normalization

问题 Without actually giving all the details of my query: Is there a way of joing the results of two separate queries on different tables? for example if i had a table result_table1 id name address 1 Joe 5 Street 2 Max 6 road 3 Jon 4 place result_table2 id occupation 1 Student 2 Lawer 3 Carpenter New table id name address occupation 1 Joe 5 Street Student 2 Max 6 road Lawer 3 Jon 4 place Carpenter If the first two tables were just tables I would use a left join, but the first two tables are

问题 I'm working on setting up a database to house properties related to a game, for example whether or not it supports multiplayer, what genres it is, release dates, etc. It seems like creating two additional tables (genres, genres_data for example) for each category type isn't nearly as dynamic as it could be. My initial thought was to set it up one of two ways... Have a games table with skeletal information, then a properties table to list all the properties, and a third table to contain all

问题 I am trying to create an object detection program in Python. The output should be the filename of the picture being analyzed, plus the "normalized coordinates" of the the object center. Each image should be normalized as follows: Top left = (0,0), Bottom left = (0,1), Top right = (1,0), Bottom right = (1,1) Any advice or suggestions on how I can normalize the coordinates of each image? 回答1: This simple function would get the job done: def normalize_coordinates(row_i, col_j, img): num_rows,

问题 Standardizing / normalizing data is an essential, if not a crucial, point when it comes to implementing machine learning algorithms. Doing so on a real time manner using Spark structured streaming has been a problem I've been trying to tackle for the past couple of weeks. Using the StandardScaler estimator ((value(i)-mean) /standard deviation) on historical data proved to be great, and in my use case it is the best, to get reasonable clustering results, but I'm not sure how to fit

问题 I heard my team leader say that in some past projects they had to do away with normalization to make the queries faster. I think it may have something to do with table unions. Is having more lean tables really less efficient than having few fat tables? 回答1: It depends ... joining tables is inherently slower than having one big table that is 'pre-joined' ie de-normalised. However, by denormalising you're going to create data duplication and your tables are going to be larger. Normalisation is

问题 I'm new to MySQL, and just learned about the importance of data normalization. My database has a simple structure: I have 1 table called users with fields: userName (string) userEmail (string) password (string) requests (an array of dictionaries in JSON string format) data (another array of dictionaries in JSON string format) deviceID (string) Right now, this is my structure. Being very new to MySQL, I'm really not seeing why my above structure is a bad idea? Why would I need to normalize

问题 I'm doing a pretty standard MySQL MATCH(...) AGAINST(...) query. I'm returning the score of each row as column score . The problem here is that score can be more than 1, so getting a percentage is tricky (multiplying by 100) due to the fact I can get scores greater than 1. My question is, can I normalise the score column so I get all scores from 0 to 1, but keep them in proportion (for example, a score of 4 would be 1, and a score of 2 would become 0.5, etc, but 4 can be a dynamic upper bound

问题 We are attempting to normalize an UIImage so that it can be passed correctly into a CoreML model. The way we are retrieving the RGB values from each pixel is by first initializing a [CGFloat] array called rawData of values for each pixel such that there is a position for the colors Red, Green, Blue and the alpha value. In bitmapInfo , we get the raw pixel values from the original UIimage itself and conduct. This is used to fill the bitmapInfo paramter in context , a CGContext variable. We

问题 I'm trying to read my text file and extract 3 main parameters and put them in separate list and apply normalizing on lists of parameters which are (Temperature, Speed, Acceleration) after assigning Gaussian distribution function. For getting good result I split up positive and negative numbers of each parameters' list and apply gaussian distribution function and pick mean value of negative numbers as the real Minimum and pick mean value of positive numbers as the real Maximum instead of

问题 I need to remove diacritics from uppercase characters in a string. Example : Électronique Caméras => Electronique Caméras (only the É is modified, é in Caméras remains as it is) I am using the following method, which removes diacritics only from the uppercase letters, but the reconstructed string looks like this - Electronique Came?ras (é is lost). How can I reconstruct the string properly? public static String removeDiacriticsFromUppercaseLetters(String input) { if (input == null) return