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;}intlbintx) {returnx (-X);}voidAddintXintV) {if(!x)return; for(intI=X;I1ll*x*v;}Long LongQues (intx) {Long LongRe=0; for(intI=x;i>0; i-=lb (i)) re+= (x+1) *c1[i]-c2[i];returnRe;}intMain () {N=read (), M=read (), P1=read (), P2=read (); a[0]=a[n+1]=n+1; s[top=1]=0; for(intI=1; i+1; i++) {if(i while(A[s[top]] for(intI=1; iintL=read (), R=read (); ans[i]+= (r-l) *p1;contribution generated by//adjacent two pointsB[i]=qwe (l,r,l-1I-1); B[i+m]=qwe (L,r,r,i,1); } sort (b+1B+1+2*M,CMP); for(intI=1; iif

. Therefore, the probability or frequency of the occurrence of the word and the word can reflect the credibility of the word better.The main statistical models are: N-ary Grammar model (N-gram), Hidden Markov model (Hidden Markov models, HMM)1.2.1n-gram model thoughtThe model is based on the assumption that the occurrence of the nth word is only related to the first N-1 word, but not to any other word, and the probability of the whole sentence is the product of the probability of each word appea

is at best marginal. For example, for workload estimates and defect forecasts, simpler data mining can achieve the same, or even better, results than the more sophisticated. 1,2 Landscape excavation Algorithm mining is "jump to see", the researcher threw the algorithm on the data, and then see what the result is. The second way is to "see and then jump", mining the data to find the possible reasoning space, and then with the learning device leap. This is the "landscape" of the data. Figure

. Starts with a set of words (start with some vocabulary):ν= {The, a, doctorate, candidate, professors, grill, cook, ask, ...}II. Get a training sample with the vocabulary set V-off (get a training sample of V):Grill Doctorate candidate.Cook professors.Ask professors.......Iii. hypothesis (assumption): The training sample is characterized by some hidden distribution p (training sample is drawn from some underlying distribution p)Iv. Objective (GOAL): Learning a probability distribution P prime a

1.bzoj1489->It's a new routine.We want to find the smallest x, then we can divide x and then determine if the average of the Benquan is less than or equal to X.The Benquan of the ring are sequentially w1,w2,w3,...,wk, the average is P,Then there are p= (W1+W2+W3+...+WK)/k,Can be launched P*K=W1+W2+W3+...+WK,This will have (w1-p) + (

-00001 my_test_model.index my_test_model.meta checkpoint** 2 Save a TF modelSaver = Tf.train.Saver ()Note that you need to save this model in a sessionPython1saver.save (Sess, ' my-model-name ')The complete example is: Import TensorFlow as tf w1 = tf. Variable (Tf.random_normal (shape=[2]), name= ' W1 ') w2 = tf. Variable (Tf.random_normal (shape=[5]), name= ' W2 ') saver = Tf.train.Saver () sess = tf. Sess

) = "Fifty" Z (6) = "Sixty" Z (7) = "Seventy" Z (8) = "Eighty" Z (9) = "Ninety" Zr1=z (MID (y,2,1)) End Function function dw (y) ' Prepare data Dim Z (5) Z (0) = "" Z (1) = "thousand" Z (2) = "Million" Z (3) = "billion" Dw=z (y) End Function function W2 (y) ' used to make 2 digits to English If MID (y,2,1) = "0" Then ' is judged to be less than 10 Value=zr3 (y) ElseIf MID (y,2,1) = "1" then "judge whether between ten to 20 VALUE=ZR2 (y) ElseIf

() "M_train=train_x_orig.shape[0" num_px=train_x_orig.shape[1] m_test=test_x_orig.shape[0] Print ("number of training Examples: "+ str (m_train)) print (" Number of testing Examples: "+ str (m_test)) print (" Each image is of size : ("+ str (NUM_PX) +", "+ str (NUM_PX) +", 3) ") Print (" Train_x_orig shape: "+ str (train_x_orig.shape)) print (" train_y Shape: "+ str (train_y.shape)) print (" Test_x_orig shape: "+ str (test_x_orig.shape) Print ("test_y shape:" + str (test_y.shape)) Train_x_flat

Tags: query data Family Order font RGB strong Mon include 1. Paging Oracle: SELECT * FROM (select A.*, ROWNUM RN from (select t.* to Sj_receiptinfo T WHERE t.taxno like CONCAT ('% ', CONCAT (?, '% ')) ORDER BY t.id Desc) A WHERE ROWNUM ) WHERE RN >? MySQL: SELECT * from TableName whereconditionsLimit( Current page number*page Capacity-1) , page Capacity pagesize SQL Server : Select W2.N, w1.* from article W1, (select TOP 1030 row_number ()

: (UIApplication *) application didfinishlaunchingwithoptions: (Nsdictionary *) launchoptions{//1. Create UIWindow Self.window = [[UIWindow alloc] initwithframe:[[uiscreen mainscreen] bounds]]; Sets the background color of the UIWindow Self.window.backgroundColor = [Uicolor Redcolor]; Let the UIWindow show (let the window become the main window and show it)//an application can have only one main window [Self.window makekeyandvisible]; Let UIWindow become the main window//[Self.wi

,:]*datamatrix[j,:]. t-labelmat[j]* (Alphas[j]-alphajold) *datamatrix[j,:]*Datamatrix[j,:]. T59if (0 and (C > Alphas[i]): b =B160Elif (0 and (C > Alphas[j]): b =B261Else:b = (B1+B2)/2.0Alphapairschanged + = 163Print"ITER:%d i:%d, pairs changed%d" %(ITER, I, alphapairschanged))64if (alphapairschanged = = 0): iter + = 165Else:iter =066Print"Iteration Number:%d" %Iter67ReturnB, Alphas6869DefDraw (Alpha, bet, data, label):Plt.xlabel (U"X1") Plt.xlim (0, +) plt.ylabel (U "x2")---I in range (Len label

. Description of main window and sub-windowCode:Once the program is started, it will be called once-(BOOL) Application: (UIApplication *) application didfinishlaunchingwithoptions: (Nsdictionary *) launchoptions{//1. Create UIWindow Self.window = [[UIWindow alloc] initwithframe:[[uiscreen mainscreen] bounds]]; Sets the background color of the UIWindow Self.window.backgroundColor = [Uicolor Redcolor]; Let the UIWindow show (let the window become the main window and show it)//an applicati

method. similarly, only a method in the same class can call a private method. the inherited subclass cannot access the private member of the parent class. Note that any member or instance of the class can access the private member. see example 6.8. The equals method compares two widgets. = the operator compares two objects in the same class, but in this example, each object instance has a unique ID. the equals method only compares name and price. note how the equals method accesses the private

: (UIApplication *) application didfinishlaunchingwithoptions: (Nsdictionary *) launchoptions{//1. Create UIWindow Self.window = [[UIWindow alloc] initwithframe:[[uiscreen mainscreen] bounds]]; Sets the background color of the UIWindow Self.window.backgroundColor = [Uicolor Redcolor]; Let the UIWindow show (let the window become the main window and show it)//an application can have only one main window [Self.window makekeyandvisible]; Let UIWindow become the main window//[Self.wi

calculated the following values:racc– the current value of the accelerometer readrgyro– based on rest (-1) and current gyroscope read valuesWhich value do we update with rest (n)? As you might have guessed, both are used. We will use a weighted average value to:Rest (n) = (RACC * W1 + rgyro * W2)/(W1 + w2)The numerator denominator is divided by W1, and the formula can be simplified into:Rest (n) = (RACC *

directly from the corpus. Commonly used is two yuan of Bi-gram and ternary tri-gram.Before introducing the N-gram model, let's start with a Shannon game (Shannon). We give a word and guess what the next word is. What's the next word you think about when I say the word "photo scandal"? I think everyone will probably think of "Edison", basically no one think of "Chen Zhijie" it. This is the main idea of the N-gram model.For a sentence T, how do we calculate the probability of its occurrence? Supp

File read/write order question this post was last edited by o911016 from 2013-03-1312: 45: 07 lt ;? Phpfunction nbsp; read ($ filename) nbsp; {$ fp nbsp; fopen ($ filename, nbsp; rb); flock ($ fp, nbsp; LOCK_SH); $ dat file read/write order This post was last edited by o911016 at 12:45:07 Function read ($ filename ){$ Fp = fopen ($ filename, 'RB ');Flock ($ fp, LOCK_SH );$ Data = @ fread ($ fp, @ filesize ($ filename ));Fclose ($ fp );Return $ data;}Function write ($ filename, $ data )

of all loops of n}. The members in S are marked as (W1, W2 ,......, And remember Wn + 1 = W1. The initial solution can be (1 ,......, N)The target function at this time is the total length of the path to access all cities or the cost function: We require the minimum value of this cost function.The generation of the new solution randomly generates two different K and M values between 1 and N. If K (W1, W2 ,

inherited subclass cannot access the private member of the parent class. Note that any member or instance of the class can access the private member. see example 6.8. The equals method compares two widgets. = The operator compares two objects in the same class, but in this example, each object instance has a unique ID. the equals method only compares name and price. note how the equals method accesses the private attribute of another widget instance. both Java and C allow such operations. L

, which is {1 ,......, A set of all loops of n}. The members in S are marked as (W1, W2 ,......, And remember Wn + 1 = W1. The initial solution can be (1 ,......, N)The target function at this time is the total length of the path to access all cities or the cost function:We require the minimum value of this cost function.The generation of the new solution randomly generates two different K and m between 1 and N. If K (W1,