reshape

Machine Learning: Predict second dataset on behalf of first dataset trained classifier

由 六眼飞鱼酱① 提交于 2020-02-02 13:06:49
问题 i am new to "Machine Learning" and tried to implement this question but it is unclear to me. its been 2 months i am Seducing, so please help me to resolve my error. Actually, i am trying to: "Train svm classifer" on TRAIN_features and TRAIN_labels extracted from TRAIN_dataset of shape (98962,) and size 98962 "Test svm classifer" on TEST_features extracted from another dataset i.e TEST_dataset of the same shape (98962,) and size 98962 as TRAIN_dataset is. After "preprocessing" of both "TRAIN

Machine Learning: Predict second dataset on behalf of first dataset trained classifier

由 随声附和 提交于 2020-02-02 13:06:11
问题 i am new to "Machine Learning" and tried to implement this question but it is unclear to me. its been 2 months i am Seducing, so please help me to resolve my error. Actually, i am trying to: "Train svm classifer" on TRAIN_features and TRAIN_labels extracted from TRAIN_dataset of shape (98962,) and size 98962 "Test svm classifer" on TEST_features extracted from another dataset i.e TEST_dataset of the same shape (98962,) and size 98962 as TRAIN_dataset is. After "preprocessing" of both "TRAIN

朝花夕拾之Matlab矩阵运算

由 不羁岁月 提交于 2020-01-29 15:21:44
矩阵运算 1. 加、减运算 运算符：“＋”和“－”分别为加、减运算符。 运算规则：对应元素相加、减，即按线性代数中矩阵的“十”，“一”运算进行。 例1-22 >>A=[1, 1, 1; 1, 2, 3; 1, 3, 6] >>B=[8, 1, 6; 3, 5, 7; 4, 9, 2] >>A＋B=A+B >>A-Ｂ=A-B 结果显示：A+B= 9 2 7 4 7 10 5 12 8 A－B= -7 0 -5 -2 -3 -4 -3 -6 4 2. 乘法 运算符：* 运算规则：按线性代数中矩阵乘法运算进行，即放在前面的矩阵的各行元素，分别与放在后面的矩阵的各列元素对应相乘并相加。 1．两个矩阵相乘 例1-23 >>X= [2 3 4 5; 1 2 2 1]； >>Y=[0 1 1; 1 1 0; 0 0 1; 1 0 0]； Z=X*Y 结果显示为： Z= 8 5 6 3 3 3 2．矩阵的数乘：数乘矩阵 上例中：a=2*X 则显示：a = 4 6 8 10 2 4 4 2 向量的点乘（内积）：维数相同的两个向量的点乘。 数组乘法： A.*B表示A与B对应元素相乘。 3 ．向量点积 函数 dot 格式 C = dot(A,B) %若A、B为向量，则返回向量A与B的点积，A与B长度相同；若为矩阵，则A与B有相同的维数。 C = dot(A,B,dim) %在dim维数中给出A与B的点积

reshape2: multiple results of aggregation function?

由 爱⌒轻易说出口 提交于 2020-01-29 03:07:47
问题 From what I read, *cast operations in reshape2 lost their result_variable feature. Hadley hints at using plyr for this purpose (appending multiple result columns to the input data frame). How would I realize the documentation example ... aqm <- melt(airquality, id=c("month", "day"), na.rm=TRUE) cast(aqm, month ~ variable + result_variable, range) using reshape2 ( dcast ) and plyr ( ddply )? 回答1: This question has multiple answers, due to the flexibility of the 'reshape2' and 'plyr' packages.

reshape2: multiple results of aggregation function?

由 孤街浪徒 提交于 2020-01-29 03:07:05
问题 From what I read, *cast operations in reshape2 lost their result_variable feature. Hadley hints at using plyr for this purpose (appending multiple result columns to the input data frame). How would I realize the documentation example ... aqm <- melt(airquality, id=c("month", "day"), na.rm=TRUE) cast(aqm, month ~ variable + result_variable, range) using reshape2 ( dcast ) and plyr ( ddply )? 回答1: This question has multiple answers, due to the flexibility of the 'reshape2' and 'plyr' packages.

R: reshaping wide to long [duplicate]

由 与世无争的帅哥 提交于 2020-01-28 11:21:46
问题 This question already has answers here : Reshaping multiple sets of measurement columns (wide format) into single columns (long format) (7 answers) Closed 2 years ago . I have a wide dataframe that looks something like this: ID Time Amount CabMean CabNum PartMean PartNum DinnMean DinNum Ex 1 1 1 27 0.654621546 8 NA 7 0.316791872 6 0 2 1 2 82 0.667461321 3 0.327594876 4 0.346798127 2 1 3 1 3 52 0.313976132 1 NA 6 0.197837257 7 0 4 1 4 99 0.798328712 9 0.913751678 4 0.191679538 9 1 I would like

Pandas: how to create a running count column?

由 懵懂的女人 提交于 2020-01-24 20:50:09
问题 I have a flat text file of the form (column headers added by me) CASE Diagnosis S1 no diagnosis S2 fungus squamous lesion S3 fungus S4 squamous lesion glandular lesion atypia I would like to stack and unstack cases with multiple diagnoses, so I would like CASE DxN Diagnosis S1 A no diagnosis S2 A fungus B squamous lesion S3 A fungus S4 A squamous lesion B glandular lesion C atypia and CASE A B C S1 no diagnosis S2 fungus squamous lesion S3 fungus S4 squamous lesion glandular lesion atypia how

OpenCV 3D Mat to Vector

由 二次信任 提交于 2020-01-24 12:53:52
问题 I have 3D Mat and would like to convert it to Vector. I tried opencv's reshape() function but it seems to not work with matrices that have dimensions more than 2. How can I convert to 3D Mat to Vector ? I can do it by accessing all elements in the Mat. Is there any efficient way? 回答1: If we have the following 3D matrix: const int ROWS=2, COLS=3, PLANES=4; int dims[3] = {ROWS, COLS, PLANES}; cv::Mat m = cv::Mat(3, dims, CV_32SC1); // works with other types (e.g. float, double,...) This only

Reshape in R without aggregation (for example MTurk response strings)

由 前提是你 提交于 2020-01-21 12:51:56
问题 Ordinarily, I'd use a pretty basic long-to-wide reshape for this, but it seems to be dropping my aggregation variables. The setup is I had a job on mechanical Turk that I performed in triplicate---I want MTurk1, Mturk2, MTurk3's answers to be their own variables in the data frame but uniquely id'd by a field I input with the job, so that I can compare them against each other with a function later. Current Format: > head(mturk) AssignmentStatus Input.id Input.State Answer.Q1thing 1 Approved

Reshape in R without aggregation (for example MTurk response strings)

由 无人久伴 提交于 2020-01-21 12:50:23
问题 Ordinarily, I'd use a pretty basic long-to-wide reshape for this, but it seems to be dropping my aggregation variables. The setup is I had a job on mechanical Turk that I performed in triplicate---I want MTurk1, Mturk2, MTurk3's answers to be their own variables in the data frame but uniquely id'd by a field I input with the job, so that I can compare them against each other with a function later. Current Format: > head(mturk) AssignmentStatus Input.id Input.State Answer.Q1thing 1 Approved
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