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--Observer mode 13th chapter The "Regret medicine" in programming--the 14th chapter of the memo mode solves the problem "third party"--the Iterator mode 15th chapter catches the problem core--Template Method Model 16th Chapter Visitor Mode 17th Chapter "and the Thing"--the intermediary mode 18th Chapter Programming Good helper--agent mode 19th Combination mode 20th Handy "adhesives"--Adapter mode 21st Chapter Decoration mode 22nd object sharing, avoid creating multi-object--Enjoy meta-mode 23rd
Textillate.js is a powerful text plug-in, if combined with ANIMATE.CSS, fittext, lettering with the use, so that the text effect is perfect.Online exampleExample DemoHow to use id="Texts">Welcome to shouce Copy $(function() { $(' #texts ').fittext (3.2,maxfontsize:18textillate ({initialdelay: 1000,in{delay: 3,shuffle :trueNBSP; }) CopyDetailed parameters Parameters Describe Default value Selector Target
replaces the maximum of inter-class distance by theminimization of hinge loss O F Top-push comparison, so thatour model have imposed much more powerful constraint onthe inter-class modeling. ApproachIn front of so many, the method is very simple, the following formula is solved:， y i is the first i A label for the sample, x i → Represents the first i A sample,
8. Support Vector machines (SVMs) Content 8. Support Vector machines (SVMs) 8.1 Optimization Objection 8.2 Large Margin Intuition 8.3 Mathematics Behind Large Margin classification 8.4 Kernels 8.5 Using a SVM 8.5.1 Multi-Class Classification 8.5.2 Logistic Regression vs. SVMs 8.1 Optimization ObjectionSupport Vector Machine (Support Vector MACHINE:SVM) is a very useful supervised machine learning algorithm. First review the logistic regression, a
segmentation of dimensions for a particular application is highly flexible and improves the efficiency of data (especially sparse data) analysis. Six, OLAP multidimensional data analysis1. Slicing and dicing (Slice and Dice)In the multidimensional data structure, by two-dimensional slicing, three-dimensional cutting, you can get the required data. such as in the ldquo; city, product, time rdquo; three-dimensional cube in the cut and slicing, can get the city, the sales of products.2. Drilling (
-deep-learning-a-part-of-artificial-intelligence.htmlHttp://deeplearning.net/deep-learning-research-groups-and-labs This have led Yann LeCun and Yoshua Bengio to create a new conference on the subject. They called it theInternational Conference on Learning Representations (ICLR), to broaden the scope from just deep learning to the more general subject of representation learning (which includes Topics such as sparse coding, that learns shallow representations, because shallow representation-learn
image, each produces a feature map, (2), Pooling (Pooling), (3), Local Response Normalization (LRN), (4), Im2col.Loss Layers:loss Drive Learning compares one output to one target and assigns cost to minimize. The loss itself is computed through the forward transmission, the gradient to the loss is computed through the rear-to-back transmission:(1), Softmax (Softmaxwithloss), (2), Sum-of-squares/euclidean (Euclideanloss), (3), Hinge/margin (Hingeloss)
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logistic regression is used, the loss function can form a convex function.Polynomial spline function fittingPolynomial fitting, the model is a polynomial form, the spline function, the model is not only continuous, but also at the boundary, the derivatives number is continuous. Benefits: is a smooth curve that avoids the appearance of turbulence in the boundary (Runge linear)Http://baike.baidu.com/view/301735.htmHere are a few concepts that need to be understood slowly:Unstructured predictive M
While it is true that Git is selected as a version control tool by many important software, it does not only work with these important software, it can also manage your shopping list (if they are important to you, of course!), your profile, weekly or diary, project progress log, or even source code!It is necessary to use Git, after all, you must have been crazy about a backup file that was not able to identify the publication of this information.Git can't help you unless you start using it, and
1, open word2007 then we click on the "page layout" screen below the "Page Setup" and then we find "margin", as shown in the following figure. 2, after entering, we click on the "Custom margin" option, open. 3, find "Custom margin" "multi-page"-"normal". 4. In the Gutter box, enter the width of the gutter margin. 5, in the Gutter position box, click Left or Top. Note: The Gutter position box is not available when you use symmetric margin, tile, or hin
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: azky876 "A group of green light in the mid-air speeding, forward fast disease fly away, it is green kite Feizhou. 下方的地面仍然是呈现出红色，地形也和一开始基本没有什么变化，到处都是一片荒芜平原，毫无生机。 唯一有些变化的，是半空中开始浮现出一团团红云，有的大有的小，静静悬浮在半空，也不随着荒原上的风游走，看起来有些诡异。 飞舟之上，韩立盘膝而坐，手中拿着一块玉简，贴在额头上。 这玉简是一副地图，他当日看过6雨晴的那副仙府地图，凭借记忆临摹画出的，虽然没有肯定比不上原图，不过也有七八成相像。 他一边观察周围的地形，一边对照着地图，试图找到此处所在的位置，可惜已经找了这些天，始终无法在地图上找到这红色荒原所在。 他眉头微皱，取下了额头的玉简。 “找不到又有什么关系，正是要什么都不知道才有意思呀！”金童有些无精打采的躺在一旁，打了一个哈欠，说道。 韩立没有理会金童，面露沉吟之色。 他可没有金童那种心态。
0. The second part of the calculation [11-13+10] gets 8. Although the correct classification of the score is higher than the incorrect classification score (13>11), but the boundary value is smaller than 10, the difference is only 2, which is why the loss value equals 8. In short, the loss function of SVM wants to correctly classify the category of fractions higher than the incorrect category score, and at least high. If this is not satisfied, the loss value starts to be calculated.So in this m
. This simplification has the following equationLinearization ofThe mathematical model that is pushed out includes the nonlinear difference equation. As a rule, the controller is designed only as a linear system, so the equation must be linearized.Consider the thrust of a shaft and a slight changeAssuming that the thrust produced by the hinge is equal to the gravity of the four rotorsUsing the Taylor expansion, you can make the mathematical model
habitual distance) is usually denoted by J, and J is kg m2. For a particle, J = M R2, where m is its mass and r is the vertical distance of the particle and the hinge. We have the inertia of electrons (even the solid ball body) when the primitive point of reference of a slowly rotating electron planet is made:Je = 2me R^2/5 = 9.11E-31 * 2.81E-21 * 0.4 = 1.024E-50 kg m2.The following assumptions, which cannot be taken seriously, are for reference only
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of the brain, which is conducive to work. IBM uses hinge fixed base design on screen shaft designOne advantage of this design is that the screen can be opened and closed at any angle, which is not easy to do. If you don't believe it, you can take other laptops. When the angle between the keyboard and the screen is less than 30 degrees, many laptops will find that the screen is automatically closed due to gravity, but IBM will not. Another advantage
as three-dimensional vector, then the vector part of two four is αβ =-α,β +αxβ, so that four yuan a = α + d1,b = C7>β + D2, thenAB =-α•beta +αxbeta + d2α + D1Beta + d1d2 = (d1a2–c1b2 + B1C2 + a1d2) i + (c1a2 + d1b2–a1c2 + b1d2) J + (-b1a2 + a1b2 + d1c2 + c1d2) k –a1a2–b1b2–c1c2 + d1d27. (AB) * = b*a*8. Define the norm of four yuan A = ai + bJ + Ck + D for: | | a| | = A2 + b2 + C2 + d2 , modulo: | a| = sqrt (A2 + b2 + C2 + D2)9. Define the inverse of the four-dollar a as: A-1 = */| | a| |A-m =
model is to fit our training samples, we ask this to be minimal, which is to ask our models to fit our training data as much as possible. But as mentioned above, we not only want to ensure that the training error is minimal, we would like our model test error is small, so we need to add the second item, that is, the parameter w of the regular function Ω (W) to constrain our model as simple as possible.OK, here, if you have been in the machine learning for many years, you will find that, ouch, m
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